Nonbinary Tree-Based Phylogenetic Networks

NARCIS (Netherlands)

Jetten, L.; van Iersel, L.J.J.

2018-01-01

Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can for example

A practical algorithm for reconstructing level-1 phylogenetic networks

NARCIS (Netherlands)

Huber, K.T.; Iersel, van L.J.J.; Kelk, S.M.; Suchecki, R.

2011-01-01

Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks-a type of network

A Practical Algorithm for Reconstructing Level-1 Phylogenetic Networks

NARCIS (Netherlands)

K.T. Huber; L.J.J. van Iersel (Leo); S.M. Kelk (Steven); R. Suchecki

2010-01-01

htmlabstractRecently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks - a type of

Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Science.gov (United States)

Pardi, Fabio; Scornavacca, Celine

2015-04-01

Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Directory of Open Access Journals (Sweden)

Fabio Pardi

2015-04-01

Full Text Available Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

A program to compute the soft Robinson-Foulds distance between phylogenetic networks.

Science.gov (United States)

Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai

2017-03-14

Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.

Reconstructing phylogenetic networks using maximum parsimony.

Science.gov (United States)

Nakhleh, Luay; Jin, Guohua; Zhao, Fengmei; Mellor-Crummey, John

2005-01-01

Phylogenies - the evolutionary histories of groups of organisms - are one of the most widely used tools throughout the life sciences, as well as objects of research within systematics, evolutionary biology, epidemiology, etc. Almost every tool devised to date to reconstruct phylogenies produces trees; yet it is widely understood and accepted that trees oversimplify the evolutionary histories of many groups of organims, most prominently bacteria (because of horizontal gene transfer) and plants (because of hybrid speciation). Various methods and criteria have been introduced for phylogenetic tree reconstruction. Parsimony is one of the most widely used and studied criteria, and various accurate and efficient heuristics for reconstructing trees based on parsimony have been devised. Jotun Hein suggested a straightforward extension of the parsimony criterion to phylogenetic networks. In this paper we formalize this concept, and provide the first experimental study of the quality of parsimony as a criterion for constructing and evaluating phylogenetic networks. Our results show that, when extended to phylogenetic networks, the parsimony criterion produces promising results. In a great majority of the cases in our experiments, the parsimony criterion accurately predicts the numbers and placements of non-tree events.

The macroecology of phylogenetically structured hummingbird-plant networks

DEFF Research Database (Denmark)

González, Ana M. Martín; Dalsgaard, Bo; Nogues, David Bravo

2015-01-01

Aim To investigate the association between hummingbird–plant network structure and species richness, phylogenetic signal on species' interaction pattern, insularity and historical and current climate. Location Fifty-four communities along a c. 10,000 km latitudinal gradient across the Americas (39...... approach, we examined the influence of species richness, phylogenetic signal, insularity and current and historical climate conditions on network structure (null-model-corrected specialization and modularity). Results Phylogenetically related species, especially plants, showed a tendency to interact...... with a similar array of mutualistic partners. The spatial variation in network structure exhibited a constant association with species phylogeny (R2 = 0.18–0.19); however, network structure showed the strongest association with species richness and environmental factors (R2 = 0.20–0.44 and R2 = 0...

A new algorithm to construct phylogenetic networks from trees.

Science.gov (United States)

Wang, J

2014-03-06

Developing appropriate methods for constructing phylogenetic networks from tree sets is an important problem, and much research is currently being undertaken in this area. BIMLR is an algorithm that constructs phylogenetic networks from tree sets. The algorithm can construct a much simpler network than other available methods. Here, we introduce an improved version of the BIMLR algorithm, QuickCass. QuickCass changes the selection strategy of the labels of leaves below the reticulate nodes, i.e., the nodes with an indegree of at least 2 in BIMLR. We show that QuickCass can construct simpler phylogenetic networks than BIMLR. Furthermore, we show that QuickCass is a polynomial-time algorithm when the output network that is constructed by QuickCass is binary.

On the quirks of maximum parsimony and likelihood on phylogenetic networks.

Science.gov (United States)

Bryant, Christopher; Fischer, Mareike; Linz, Simone; Semple, Charles

2017-03-21

Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe evolution accurately. For instance, processes like hybridization or lateral gene transfer that are commonplace in many groups of organisms and result in mosaic patterns of relationships cannot be represented by a single phylogenetic tree. This is why phylogenetic networks, which can display such events, are becoming of more and more interest in phylogenetic research. It is therefore necessary to extend concepts like maximum parsimony from phylogenetic trees to networks. Several suggestions for possible extensions can be found in recent literature, for instance the softwired and the hardwired parsimony concepts. In this paper, we analyze the so-called big parsimony problem under these two concepts, i.e. we investigate maximum parsimonious networks and analyze their properties. In particular, we show that finding a softwired maximum parsimony network is possible in polynomial time. We also show that the set of maximum parsimony networks for the hardwired definition always contains at least one phylogenetic tree. Lastly, we investigate some parallels of parsimony to different likelihood concepts on phylogenetic networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quartet-net: a quartet-based method to reconstruct phylogenetic networks.

Science.gov (United States)

Yang, Jialiang; Grünewald, Stefan; Wan, Xiu-Feng

2013-05-01

Phylogenetic networks can model reticulate evolutionary events such as hybridization, recombination, and horizontal gene transfer. However, reconstructing such networks is not trivial. Popular character-based methods are computationally inefficient, whereas distance-based methods cannot guarantee reconstruction accuracy because pairwise genetic distances only reflect partial information about a reticulate phylogeny. To balance accuracy and computational efficiency, here we introduce a quartet-based method to construct a phylogenetic network from a multiple sequence alignment. Unlike distances that only reflect the relationship between a pair of taxa, quartets contain information on the relationships among four taxa; these quartets provide adequate capacity to infer a more accurate phylogenetic network. In applications to simulated and biological data sets, we demonstrate that this novel method is robust and effective in reconstructing reticulate evolutionary events and it has the potential to infer more accurate phylogenetic distances than other conventional phylogenetic network construction methods such as Neighbor-Joining, Neighbor-Net, and Split Decomposition. This method can be used in constructing phylogenetic networks from simple evolutionary events involving a few reticulate events to complex evolutionary histories involving a large number of reticulate events. A software called "Quartet-Net" is implemented and available at http://sysbio.cvm.msstate.edu/QuartetNet/.

Reconstruction of certain phylogenetic networks from their tree-average distances.

Science.gov (United States)

Willson, Stephen J

2013-10-01

Trees are commonly utilized to describe the evolutionary history of a collection of biological species, in which case the trees are called phylogenetic trees. Often these are reconstructed from data by making use of distances between extant species corresponding to the leaves of the tree. Because of increased recognition of the possibility of hybridization events, more attention is being given to the use of phylogenetic networks that are not necessarily trees. This paper describes the reconstruction of certain such networks from the tree-average distances between the leaves. For a certain class of phylogenetic networks, a polynomial-time method is presented to reconstruct the network from the tree-average distances. The method is proved to work if there is a single reticulation cycle.

Detecting Network Communities: An Application to Phylogenetic Analysis

Science.gov (United States)

Andrade, Roberto F. S.; Rocha-Neto, Ivan C.; Santos, Leonardo B. L.; de Santana, Charles N.; Diniz, Marcelo V. C.; Lobão, Thierry Petit; Goés-Neto, Aristóteles; Pinho, Suani T. R.; El-Hani, Charbel N.

2011-01-01

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis. PMID:21573202

A reconstruction problem for a class of phylogenetic networks with lateral gene transfers.

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Cardona, Gabriel; Pons, Joan Carles; Rosselló, Francesc

2015-01-01

Lateral, or Horizontal, Gene Transfers are a type of asymmetric evolutionary events where genetic material is transferred from one species to another. In this paper we consider LGT networks, a general model of phylogenetic networks with lateral gene transfers which consist, roughly, of a principal rooted tree with its leaves labelled on a set of taxa, and a set of extra secondary arcs between nodes in this tree representing lateral gene transfers. An LGT network gives rise in a natural way to a principal phylogenetic subtree and a set of secondary phylogenetic subtrees, which, roughly, represent, respectively, the main line of evolution of most genes and the secondary lines of evolution through lateral gene transfers. We introduce a set of simple conditions on an LGT network that guarantee that its principal and secondary phylogenetic subtrees are pairwise different and that these subtrees determine, up to isomorphism, the LGT network. We then give an algorithm that, given a set of pairwise different phylogenetic trees [Formula: see text] on the same set of taxa, outputs, when it exists, the LGT network that satisfies these conditions and such that its principal phylogenetic tree is [Formula: see text] and its secondary phylogenetic trees are [Formula: see text].

Efficient parsimony-based methods for phylogenetic network reconstruction.

Science.gov (United States)

Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir

2007-01-15

Phylogenies--the evolutionary histories of groups of organisms-play a major role in representing relationships among biological entities. Although many biological processes can be effectively modeled as tree-like relationships, others, such as hybrid speciation and horizontal gene transfer (HGT), result in networks, rather than trees, of relationships. Hybrid speciation is a significant evolutionary mechanism in plants, fish and other groups of species. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Maximum parsimony is one of the most commonly used criteria for phylogenetic tree inference. Roughly speaking, inference based on this criterion seeks the tree that minimizes the amount of evolution. In 1990, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to recombination. Preliminary results on small synthetic datasets. Nakhleh et al. (2005) demonstrated the criterion's application to phylogenetic network reconstruction in general and HGT detection in particular. However, the naive algorithms used by the authors are inapplicable to large datasets due to their demanding computational requirements. Further, no rigorous theoretical analysis of computing the criterion was given, nor was it tested on biological data. In the present work we prove that the problem of scoring the parsimony of a phylogenetic network is NP-hard and provide an improved fixed parameter tractable algorithm for it. Further, we devise efficient heuristics for parsimony-based reconstruction of phylogenetic networks. We test our methods on both synthetic and biological data (rbcL gene in bacteria) and obtain very promising results.

Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

Science.gov (United States)

Francis, Andrew; Moulton, Vincent

2018-06-07

Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Inference of Transmission Network Structure from HIV Phylogenetic Trees.

Science.gov (United States)

Giardina, Federica; Romero-Severson, Ethan Obie; Albert, Jan; Britton, Tom; Leitner, Thomas

2017-01-01

Phylogenetic inference is an attractive means to reconstruct transmission histories and epidemics. However, there is not a perfect correspondence between transmission history and virus phylogeny. Both node height and topological differences may occur, depending on the interaction between within-host evolutionary dynamics and between-host transmission patterns. To investigate these interactions, we added a within-host evolutionary model in epidemiological simulations and examined if the resulting phylogeny could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivity across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phylogeny (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phylogeny reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivity dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.

Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

Science.gov (United States)

Luo, Congpei; He, Tao; Chun, Ze

2013-04-01

Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.

Worst-case optimal approximation algorithms for maximizing triplet consistency within phylogenetic networks

NARCIS (Netherlands)

J. Byrka (Jaroslaw); K.T. Huber; S.M. Kelk (Steven); P. Gawrychowski

2009-01-01

htmlabstractThe study of phylogenetic networks is of great interest to computational evolutionary biology and numerous different types of such structures are known. This article addresses the following question concerning rooted versions of phylogenetic networks. What is the maximum value of pset

Autumn Algorithm-Computation of Hybridization Networks for Realistic Phylogenetic Trees.

Science.gov (United States)

Huson, Daniel H; Linz, Simone

2018-01-01

A minimum hybridization network is a rooted phylogenetic network that displays two given rooted phylogenetic trees using a minimum number of reticulations. Previous mathematical work on their calculation has usually assumed the input trees to be bifurcating, correctly rooted, or that they both contain the same taxa. These assumptions do not hold in biological studies and "realistic" trees have multifurcations, are difficult to root, and rarely contain the same taxa. We present a new algorithm for computing minimum hybridization networks for a given pair of "realistic" rooted phylogenetic trees. We also describe how the algorithm might be used to improve the rooting of the input trees. We introduce the concept of "autumn trees", a nice framework for the formulation of algorithms based on the mathematics of "maximum acyclic agreement forests". While the main computational problem is hard, the run-time depends mainly on how different the given input trees are. In biological studies, where the trees are reasonably similar, our parallel implementation performs well in practice. The algorithm is available in our open source program Dendroscope 3, providing a platform for biologists to explore rooted phylogenetic networks. We demonstrate the utility of the algorithm using several previously studied data sets.

Constructing level-2 phylogenetic networks from triplets

OpenAIRE

Iersel, Leo; Keijsper, J.C.M.; Kelk, Steven; Stougie, Leen; Hagen, F.; Boekhout, T.; Vingron, M.; Wong, L.

2009-01-01

htmlabstractJansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so to construct such a network (Inferring a Level-1 Phylogenetic Network from a Dense Set of Rooted Triplets, Theoretical Computer Science, 363, pp. 60-68 (2006)). Here we extend this work by showing that this probl...

Phylogenetic convolutional neural networks in metagenomics.

Science.gov (United States)

Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

2018-03-08

Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

Drug use Discrimination Predicts Formation of High-Risk Social Networks: Examining Social Pathways of Discrimination.

Science.gov (United States)

Crawford, Natalie D; Ford, Chandra; Rudolph, Abby; Kim, BoRin; Lewis, Crystal M

2017-09-01

Experiences of discrimination, or social marginalization and ostracism, may lead to the formation of social networks characterized by inequality. For example, those who experience discrimination may be more likely to develop drug use and sexual partnerships with others who are at increased risk for HIV compared to those without experiences of discrimination. This is critical as engaging in risk behaviors with others who are more likely to be HIV positive can increase one's risk of HIV. We used log-binomial regression models to examine the relationship between drug use, racial and incarceration discrimination with changes in the composition of one's risk network among 502 persons who use drugs. We examined both absolute and proportional changes with respect to sex partners, drug use partners, and injecting partners, after accounting for individual risk behaviors. At baseline, participants were predominately male (70%), black or Latino (91%), un-married (85%), and used crack (64%). Among those followed-up (67%), having experienced discrimination due to drug use was significantly related to increases in the absolute number of sex networks and drug networks over time. No types of discrimination were related to changes in the proportion of high-risk network members. Discrimination may increase one's risk of HIV acquisition by leading them to preferentially form risk relationships with higher-risk individuals, thereby perpetuating racial and ethnic inequities in HIV. Future social network studies and behavioral interventions should consider whether social discrimination plays a role in HIV transmission.

Phylogenetically informed logic relationships improve detection of biological network organization

Science.gov (United States)

2011-01-01

Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

IcyTree: rapid browser-based visualization for phylogenetic trees and networks.

Science.gov (United States)

Vaughan, Timothy G

2017-08-01

IcyTree is an easy-to-use application which can be used to visualize a wide variety of phylogenetic trees and networks. While numerous phylogenetic tree viewers exist already, IcyTree distinguishes itself by being a purely online tool, having a responsive user interface, supporting phylogenetic networks (ancestral recombination graphs in particular), and efficiently drawing trees that include information such as ancestral locations or trait values. IcyTree also provides intuitive panning and zooming utilities that make exploring large phylogenetic trees of many thousands of taxa feasible. IcyTree is a web application and can be accessed directly at http://tgvaughan.github.com/icytree . Currently supported web browsers include Mozilla Firefox and Google Chrome. IcyTree is written entirely in client-side JavaScript (no plugin required) and, once loaded, does not require network access to run. IcyTree is free software, and the source code is made available at http://github.com/tgvaughan/icytree under version 3 of the GNU General Public License. tgvaughan@gmail.com. © The Author(s) 2017. Published by Oxford University Press.

Computing all hybridization networks for multiple binary phylogenetic input trees.

Science.gov (United States)

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

Quartet-based methods to reconstruct phylogenetic networks.

Science.gov (United States)

Yang, Jialiang; Grünewald, Stefan; Xu, Yifei; Wan, Xiu-Feng

2014-02-20

Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate. We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China. QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.

On Unrooted and Root-Uncertain Variants of Several Well-Known Phylogenetic Network Problems

NARCIS (Netherlands)

van Iersel, L.J.J.; Kelk, Steven; Stougie, Leen; Boes, Olivier

2017-01-01

The hybridization number problem requires us to embed a set of binary rooted phylogenetic trees into a binary rooted phylogenetic network such that the number of nodes with indegree two is minimized. However, from a biological point of view accurately inferring the root location in a phylogenetic

Do Branch Lengths Help to Locate a Tree in a Phylogenetic Network?

Science.gov (United States)

Gambette, Philippe; van Iersel, Leo; Kelk, Steven; Pardi, Fabio; Scornavacca, Celine

2016-09-01

Phylogenetic networks are increasingly used in evolutionary biology to represent the history of species that have undergone reticulate events such as horizontal gene transfer, hybrid speciation and recombination. One of the most fundamental questions that arise in this context is whether the evolution of a gene with one copy in all species can be explained by a given network. In mathematical terms, this is often translated in the following way: is a given phylogenetic tree contained in a given phylogenetic network? Recently this tree containment problem has been widely investigated from a computational perspective, but most studies have only focused on the topology of the phylogenies, ignoring a piece of information that, in the case of phylogenetic trees, is routinely inferred by evolutionary analyses: branch lengths. These measure the amount of change (e.g., nucleotide substitutions) that has occurred along each branch of the phylogeny. Here, we study a number of versions of the tree containment problem that explicitly account for branch lengths. We show that, although length information has the potential to locate more precisely a tree within a network, the problem is computationally hard in its most general form. On a positive note, for a number of special cases of biological relevance, we provide algorithms that solve this problem efficiently. This includes the case of networks of limited complexity, for which it is possible to recover, among the trees contained by the network with the same topology as the input tree, the closest one in terms of branch lengths.

Inferring phylogenetic networks by the maximum parsimony criterion: a case study.

Science.gov (United States)

Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir

2007-01-01

Horizontal gene transfer (HGT) may result in genes whose evolutionary histories disagree with each other, as well as with the species tree. In this case, reconciling the species and gene trees results in a network of relationships, known as the "phylogenetic network" of the set of species. A phylogenetic network that incorporates HGT consists of an underlying species tree that captures vertical inheritance and a set of edges which model the "horizontal" transfer of genetic material. In a series of papers, Nakhleh and colleagues have recently formulated a maximum parsimony (MP) criterion for phylogenetic networks, provided an array of computationally efficient algorithms and heuristics for computing it, and demonstrated its plausibility on simulated data. In this article, we study the performance and robustness of this criterion on biological data. Our findings indicate that MP is very promising when its application is extended to the domain of phylogenetic network reconstruction and HGT detection. In all cases we investigated, the MP criterion detected the correct number of HGT events required to map the evolutionary history of a gene data set onto the species phylogeny. Furthermore, our results indicate that the criterion is robust with respect to both incomplete taxon sampling and the use of different site substitution matrices. Finally, our results show that the MP criterion is very promising in detecting HGT in chimeric genes, whose evolutionary histories are a mix of vertical and horizontal evolution. Besides the performance analysis of MP, our findings offer new insights into the evolution of 4 biological data sets and new possible explanations of HGT scenarios in their evolutionary history.

Trinets encode tree-child and level-2 phylogenetic networks

NARCIS (Netherlands)

L.J.J. van Iersel (Leo); V. Moulton

2012-01-01

htmlabstractPhylogenetic networks generalize evolutionary trees, and are commonly used to represent evolutionary histories of species that undergo reticulate evolutionary processes such as hybridization, recombination and lateral gene transfer. Recently, there has been great interest in trying to

Uniqueness, intractability and exact algorithms: reflections on level-k phylogenetic networks

NARCIS (Netherlands)

L.J.J. van Iersel (Leo); S.M. Kelk (Steven); M. Mnich

2009-01-01

htmlabstractPhylogenetic networks provide a way to describe and visualize evolutionary histories that have undergone so-called reticulate evolutionary events such as recombination, hybridization or horizontal gene transfer. The level k of a network determines how non-treelike the evolution can be,

Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

Science.gov (United States)

Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

2017-10-01

Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

Science.gov (United States)

Oh, S June; Joung, Je-Gun; Chang, Jeong-Ho; Zhang, Byoung-Tak

2006-06-06

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks

Directory of Open Access Journals (Sweden)

Chang Jeong-Ho

2006-06-01

Full Text Available Abstract Background To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. Results To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. Conclusion By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway

Object recognition with hierarchical discriminant saliency networks.

Science.gov (United States)

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

Linear programming model to construct phylogenetic network for 16S rRNA sequences of photosynthetic organisms and influenza viruses.

Science.gov (United States)

Mathur, Rinku; Adlakha, Neeru

2014-06-01

Phylogenetic trees give the information about the vertical relationships of ancestors and descendants but phylogenetic networks are used to visualize the horizontal relationships among the different organisms. In order to predict reticulate events there is a need to construct phylogenetic networks. Here, a Linear Programming (LP) model has been developed for the construction of phylogenetic network. The model is validated by using data sets of chloroplast of 16S rRNA sequences of photosynthetic organisms and Influenza A/H5N1 viruses. Results obtained are in agreement with those obtained by earlier researchers.

Inferring Phylogenetic Networks from Gene Order Data

Directory of Open Access Journals (Sweden)

Alexey Anatolievich Morozov

2013-01-01

Full Text Available Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary, sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm. Binary encoding can also be useful, but only when the methods mentioned above cannot be used.

Fire modifies the phylogenetic structure of soil bacterial co-occurrence networks.

Science.gov (United States)

Pérez-Valera, Eduardo; Goberna, Marta; Faust, Karoline; Raes, Jeroen; García, Carlos; Verdú, Miguel

2017-01-01

Fire alters ecosystems by changing the composition and community structure of soil microbes. The phylogenetic structure of a community provides clues about its main assembling mechanisms. While environmental filtering tends to reduce the community phylogenetic diversity by selecting for functionally (and hence phylogenetically) similar species, processes like competitive exclusion by limiting similarity tend to increase it by preventing the coexistence of functionally (and phylogenetically) similar species. We used co-occurrence networks to detect co-presence (bacteria that co-occur) or exclusion (bacteria that do not co-occur) links indicative of the ecological interactions structuring the community. We propose that inspecting the phylogenetic structure of co-presence or exclusion links allows to detect the main processes simultaneously assembling the community. We monitored a soil bacterial community after an experimental fire and found that fire altered its composition, richness and phylogenetic diversity. Both co-presence and exclusion links were more phylogenetically related than expected by chance. We interpret such a phylogenetic clustering in co-presence links as a result of environmental filtering, while that in exclusion links reflects competitive exclusion by limiting similarity. This suggests that environmental filtering and limiting similarity operate simultaneously to assemble soil bacterial communities, widening the traditional view that only environmental filtering structures bacterial communities. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

A measure of the denseness of a phylogenetic network. [by sequenced proteins from extant species

Science.gov (United States)

Holmquist, R.

1978-01-01

An objective measure of phylogenetic denseness is developed to examine various phylogenetic criteria: alpha- and beta-hemoglobin, myoglobin, cytochrome c, and the parvalbumin family. Attention is given to the number of nucleotide replacements separating homologous sequences, and to the topology of the network (in other words, to the qualitative nature of the network as defined by how closely the studied species are related). Applications include quantitative comparisons of species origin, relation, and rates of evolution.

Tree-average distances on certain phylogenetic networks have their weights uniquely determined.

Science.gov (United States)

Willson, Stephen J

2012-01-01

A phylogenetic network N has vertices corresponding to species and arcs corresponding to direct genetic inheritance from the species at the tail to the species at the head. Measurements of DNA are often made on species in the leaf set, and one seeks to infer properties of the network, possibly including the graph itself. In the case of phylogenetic trees, distances between extant species are frequently used to infer the phylogenetic trees by methods such as neighbor-joining. This paper proposes a tree-average distance for networks more general than trees. The notion requires a weight on each arc measuring the genetic change along the arc. For each displayed tree the distance between two leaves is the sum of the weights along the path joining them. At a hybrid vertex, each character is inherited from one of its parents. We will assume that for each hybrid there is a probability that the inheritance of a character is from a specified parent. Assume that the inheritance events at different hybrids are independent. Then for each displayed tree there will be a probability that the inheritance of a given character follows the tree; this probability may be interpreted as the probability of the tree. The tree-average distance between the leaves is defined to be the expected value of their distance in the displayed trees. For a class of rooted networks that includes rooted trees, it is shown that the weights and the probabilities at each hybrid vertex can be calculated given the network and the tree-average distances between the leaves. Hence these weights and probabilities are uniquely determined. The hypotheses on the networks include that hybrid vertices have indegree exactly 2 and that vertices that are not leaves have a tree-child.

Pulse discrimination of scintillator detector with artificial neural network

International Nuclear Information System (INIS)

Chen Man; Cai Yuerong; Yang Chaowen

2006-01-01

The features of signal for scintillator detectors are analyzed. According to the difference in the fraction of slow and fast scintillation for different particles, three intrinsic parameters (signal amplitude, integration of signal during rinsing, integration of frequency spectrum of signals in middle frequencies) of signals are defined. The artificial neural network method for pulse discrimination of scintillator detector is studied. The signals with different shapes under real condition are simulated with computer, and discriminated by the method. Results of discrimination are gotten and discussed. (authors)

Object recognition with hierarchical discriminant saliency networks

Directory of Open Access Journals (Sweden)

Sunhyoung eHan

2014-09-01

Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

Mapping and discrimination of networks in the complexity-entropy plane

Science.gov (United States)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis. Here we explore the possibility to classify complex networks by means of a statistical complexity measure that has formerly been successfully applied to distinguish different types of chaotic and stochastic time series. It is composed of a network's averaged per-node entropic measure characterizing the network's information content and the associated Jenson-Shannon divergence as a measure of disequilibrium. We study 29 real-world networks and show that networks of the same category tend to cluster in distinct areas of the resulting complexity-entropy plane. We demonstrate that within our framework, connectome networks exhibit among the highest complexity while, e.g., transportation and infrastructure networks display significantly lower values. Furthermore, we demonstrate the utility of our framework by applying it to families of random scale-free and Watts-Strogatz model networks. We then show in a second application that the proposed framework is useful to objectively construct threshold-based networks, such as functional climate networks or recurrence networks, by choosing the threshold such that the statistical network complexity is maximized.

Sonar discrimination of cylinders from different angles using neural networks neural networks

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Au, Whiwlow; Larsen, Jan

1999-01-01

This paper describes an underwater object discrimination system applied to recognize cylinders of various compositions from different angles. The system is based on a new combination of simulated dolphin clicks, simulated auditory filters and artificial neural networks. The model demonstrates its...

Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees.

Science.gov (United States)

Mirzaei, Sajad; Wu, Yufeng

2016-01-01

Hybridization networks represent plausible evolutionary histories of species that are affected by reticulate evolutionary processes. An established computational problem on hybridization networks is constructing the most parsimonious hybridization network such that each of the given phylogenetic trees (called gene trees) is "displayed" in the network. There have been several previous approaches, including an exact method and several heuristics, for this NP-hard problem. However, the exact method is only applicable to a limited range of data, and heuristic methods can be less accurate and also slow sometimes. In this paper, we develop a new algorithm for constructing near parsimonious networks for multiple binary gene trees. This method is more efficient for large numbers of gene trees than previous heuristics. This new method also produces more parsimonious results on many simulated datasets as well as a real biological dataset than a previous method. We also show that our method produces topologically more accurate networks for many datasets.

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

Science.gov (United States)

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns-both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity.

Phylogenetic Trees and Networks Reduce to Phylogenies on Binary States: Does It Furnish an Explanation to the Robustness of Phylogenetic Trees against Lateral Transfers.

Science.gov (United States)

Thuillard, Marc; Fraix-Burnet, Didier

2015-01-01

This article presents an innovative approach to phylogenies based on the reduction of multistate characters to binary-state characters. We show that the reduction to binary characters' approach can be applied to both character- and distance-based phylogenies and provides a unifying framework to explain simply and intuitively the similarities and differences between distance- and character-based phylogenies. Building on these results, this article gives a possible explanation on why phylogenetic trees obtained from a distance matrix or a set of characters are often quite reasonable despite lateral transfers of genetic material between taxa. In the presence of lateral transfers, outer planar networks furnish a better description of evolution than phylogenetic trees. We present a polynomial-time reconstruction algorithm for perfect outer planar networks with a fixed number of states, characters, and lateral transfers.

Neural network modeling of a dolphin's sonar discrimination capabilities

OpenAIRE

Andersen, Lars Nonboe; René Rasmussen, A; Au, WWL; Nachtigall, PE; Roitblat, H.

1994-01-01

The capability of an echo-locating dolphin to discriminate differences in the wall thickness of cylinders was previously modeled by a counterpropagation neural network using only spectral information of the echoes [W. W. L. Au, J. Acoust. Soc. Am. 95, 2728–2735 (1994)]. In this study, both time and frequency information were used to model the dolphin discrimination capabilities. Echoes from the same cylinders were digitized using a broadband simulated dolphin sonar signal with the transducer ...

Phylogenetic Trees and Networks Reduce to Phylogenies on Binary States: Does It Furnish an Explanation to the Robustness of Phylogenetic Trees against Lateral Transfers

Science.gov (United States)

Thuillard, Marc; Fraix-Burnet, Didier

2015-01-01

This article presents an innovative approach to phylogenies based on the reduction of multistate characters to binary-state characters. We show that the reduction to binary characters’ approach can be applied to both character- and distance-based phylogenies and provides a unifying framework to explain simply and intuitively the similarities and differences between distance- and character-based phylogenies. Building on these results, this article gives a possible explanation on why phylogenetic trees obtained from a distance matrix or a set of characters are often quite reasonable despite lateral transfers of genetic material between taxa. In the presence of lateral transfers, outer planar networks furnish a better description of evolution than phylogenetic trees. We present a polynomial-time reconstruction algorithm for perfect outer planar networks with a fixed number of states, characters, and lateral transfers. PMID:26508826

Broccoli/weed/soil discrimination by optical reflectance using neural networks

Science.gov (United States)

Hahn, Federico

1995-04-01

Broccoli is grown extensively in Scotland, and has become one of the main vegetables cropped, due to its high yields and profits. Broccoli, weed and soil samples from 6 different farms were collected and their spectra obtained and analyzed using discriminant analysis. High crop/weed/soil discrimination success rates were encountered in each farm, but the selected wavelengths varied in each farm due to differences in broccoli variety, weed species incidence and soil type. In order to use only three wavelengths, neural networks were introduced and high crop/weed/soil discrimination accuracies for each farm were achieved.

Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences

Science.gov (United States)

Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence d...

Neural network modeling of a dolphin's sonar discrimination capabilities

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; René Rasmussen, A; Au, WWL

1994-01-01

The capability of an echo-locating dolphin to discriminate differences in the wall thickness of cylinders was previously modeled by a counterpropagation neural network using only spectral information of the echoes [W. W. L. Au, J. Acoust. Soc. Am. 95, 2728–2735 (1994)]. In this study, both time a...

Inferring influenza global transmission networks without complete phylogenetic information.

Science.gov (United States)

Aris-Brosou, Stéphane

2014-03-01

Influenza is one of the most severe respiratory infections affecting humans throughout the world, yet the dynamics of its global transmission network are still contentious. Here, I describe a novel combination of phylogenetics, time series, and graph theory to analyze 14.25 years of data stratified in space and in time, focusing on the main target of the human immune response, the hemagglutinin gene. While bypassing the complete phylogenetic inference of huge data sets, the method still extracts information suggesting that waves of genetic or of nucleotide diversity circulate continuously around the globe for subtypes that undergo sustained transmission over several seasons, such as H3N2 and pandemic H1N1/09, while diversity of prepandemic H1N1 viruses had until 2009 a noncontinuous transmission pattern consistent with a source/sink model. Irrespective of the shift in the structure of H1N1 diversity circulation with the emergence of the pandemic H1N1/09 strain, US prevalence peaks during the winter months when genetic diversity is at its lowest. This suggests that a dominant strain is generally responsible for epidemics and that monitoring genetic and/or nucleotide diversity in real time could provide public health agencies with an indirect estimate of prevalence.

Time-of-flight discrimination between gamma-rays and neutrons by using artificial neural networks

International Nuclear Information System (INIS)

Akkoyun, S.

2013-01-01

Highlights: ► Time-of-flight (tof) is an obvious method for separation between gamma and neutron particles. ► tof distributions are obtained by neural networks. ► Neural network method is consistent with the experimental results. ► Neural networks can classify different events for discrimination. - Abstract: In gamma-ray spectroscopy, a number of neutrons are emitted from the nuclei together with the gamma-rays. These neutrons influence gamma-ray spectra. An obvious method for discrimination between neutrons and gamma-rays is based on the time-of-flight (tof) technique. In this work, the tof distributions of gamma-rays and neutrons were obtained both experimentally and by using artificial neural networks (ANNs). It was shown that, ANN can correctly classify gamma-ray and neutron events. Also, for highly nonlinear detector response for tof, we have constructed consistent empirical physical formulas (EPFs) by appropriate ANNs. These ANN–EPFs can be used to derive further physical functions which could be relevant to discrimination between gamma-rays and neutrons

Discriminative topological features reveal biological network mechanisms

Directory of Open Access Journals (Sweden)

Levovitz Chaya

2004-11-01

Full Text Available Abstract Background Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and sociological origin. In most cases the success of a model has been evaluated by how well it reproduces a few key features of the real-world data, such as degree distributions, mean geodesic lengths, and clustering coefficients. Often pairs of models can reproduce these features with indistinguishable fidelity despite being generated by vastly different mechanisms. In such cases, these few target features are insufficient to distinguish which of the different models best describes real world networks of interest; moreover, it is not clear a priori that any of the presently-existing algorithms for network generation offers a predictive description of the networks inspiring them. Results We present a method to assess systematically which of a set of proposed network generation algorithms gives the most accurate description of a given biological network. To derive discriminative classifiers, we construct a mapping from the set of all graphs to a high-dimensional (in principle infinite-dimensional "word space". This map defines an input space for classification schemes which allow us to state unambiguously which models are most descriptive of a given network of interest. Our training sets include networks generated from 17 models either drawn from the literature or introduced in this work. We show that different duplication-mutation schemes best describe the E. coli genetic network, the S. cerevisiae protein interaction network, and the C. elegans neuronal network, out of a set of network models including a linear preferential attachment model and a small-world model. Conclusions Our method is a first step towards systematizing network models and assessing their predictability, and we anticipate its usefulness for a number of communities.

Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences.

Science.gov (United States)

Zheng, Xiaoyan; Cai, Danying; Potter, Daniel; Postman, Joseph; Liu, Jing; Teng, Yuanwen

2014-11-01

Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence datasets. Phylogenetic trees based on both cpDNA and nuclear LFY2int2-N (LN) data resulted in poor resolution, especially, only five primary species were monophyletic in the LN tree. A phylogenetic network of LN suggested that reticulation caused by hybridization is one of the major evolutionary processes for Pyrus species. Polytomies of the gene trees and star-like structure of cpDNA networks suggested rapid radiation is another major evolutionary process, especially for the occidental species. Pyrus calleryana and P. regelii were the earliest diverged Pyrus species. Two North African species, P. cordata, P. spinosa and P. betulaefolia were descendent of primitive stock Pyrus species and still share some common molecular characters. Southwestern China, where a large number of P. pashia populations are found, is probably the most important diversification center of Pyrus. More accessions and nuclear genes are needed for further understanding the evolutionary histories of Pyrus. Copyright © 2014 Elsevier Inc. All rights reserved.

Phylogenetic trait-based analyses of ecological networks.

Science.gov (United States)

Rafferty, Nicole E; Ives, Anthony R

2013-10-01

Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out

Neural network consistent empirical physical formula construction for neutron–gamma discrimination in gamma ray tracking

International Nuclear Information System (INIS)

Yildiz, Nihat; Akkoyun, Serkan

2013-01-01

Highlights: ► Detector responses in neutron–gamma discrimination were estimated by neural networks. ► Novel consistent neural network empirical physical formulas (EPFs) were constructed for detector responses. ► The EPFs are of explicit mathematical functional form. ► The EPFs can be used to derive various physical functions relevant to neutron–gamma discrimination in gamma ray tracking. -- Abstract: Gamma ray tracking is an efficient detection technique in studying exotic nuclei which lies far from beta stability line. To achieve very powerful and extraordinary resolution ability, new detectors based on gamma ray tracking are currently being developed. To reach this achievement, the neutron–gamma discrimination in these detectors is also an important task. In this paper, by suitable layered feedforward neural networks (LFNNs), we have constructed novel and consistent empirical physical formulas (EPFs) for some highly nonlinear detector counts measured in neutron–gamma discrimination. The detector counts data used in the discrimination was actually borrowed from our previous paper. The counts used here had been originally measured versus the following parameters: energy deposited in the first interaction points, difference in the incoming direction of initial gamma rays, and finally figure of merit values of the clusters determined by tracking. The LFNN–EPFs are of explicit mathematical functional form. Therefore, by various suitable operations of mathematical analysis, these LFNN–EPFs can be used to derivate further physical functions which might be potentially relevant to neutron–gamma discrimination performance of gamma ray tracking.

Spatiotemporal discrimination in neural networks with short-term synaptic plasticity

Science.gov (United States)

Shlaer, Benjamin; Miller, Paul

2015-03-01

Cells in recurrently connected neural networks exhibit bistability, which allows for stimulus information to persist in a circuit even after stimulus offset, i.e. short-term memory. However, such a system does not have enough hysteresis to encode temporal information about the stimuli. The biophysically described phenomenon of synaptic depression decreases synaptic transmission strengths due to increased presynaptic activity. This short-term reduction in synaptic strengths can destabilize attractor states in excitatory recurrent neural networks, causing the network to move along stimulus dependent dynamical trajectories. Such a network can successfully separate amplitudes and durations of stimuli from the number of successive stimuli. Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression. Front. Comput. Neurosci. 7:59., and so provides a strong candidate network for the encoding of spatiotemporal information. Here we explicitly demonstrate the capability of a recurrent neural network with short-term synaptic depression to discriminate between the temporal sequences in which spatial stimuli are presented.

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

Directory of Open Access Journals (Sweden)

Junha Shin

Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

The algebra of the general Markov model on phylogenetic trees and networks.

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Sumner, J G; Holland, B R; Jarvis, P D

2012-04-01

It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the “splitting” operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications.

Dynamic functional brain networks involved in simple visual discrimination learning.

Science.gov (United States)

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Phylogenetic versus functional signals in the evolution of form-function relationships in terrestrial vision.

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Motani, Ryosuke; Schmitz, Lars

2011-08-01

Phylogeny is deeply pertinent to evolutionary studies. Traits that perform a body function are expected to be strongly influenced by physical "requirements" of the function. We investigated if such traits exhibit phylogenetic signals, and, if so, how phylogenetic noises bias quantification of form-function relationships. A form-function system that is strongly influenced by physics, namely the relationship between eye morphology and visual optics in amniotes, was used. We quantified the correlation between form (i.e., eye morphology) and function (i.e., ocular optics) while varying the level of phylogenetic bias removal through adjusting Pagel's λ. Ocular soft-tissue dimensions exhibited the highest correlation with ocular optics when 1% of phylogenetic bias expected from Brownian motion was removed (i.e., λ= 0.01); the value for hard-tissue data were 8%. A small degree of phylogenetic bias therefore exists in morphology despite of the stringent functional constraints. We also devised a phylogenetically informed discriminant analysis and recorded the effects of phylogenetic bias on this method using the same data. Use of proper λ values during phylogenetic bias removal improved misidentification rates in resulting classifications when prior probabilities were assumed to be equal. Even a small degree of phylogenetic bias affected the classification resulting from phylogenetically informed discriminant analysis. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Feature extraction with deep neural networks by a generalized discriminant analysis.

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Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

Discriminating lysosomal membrane protein types using dynamic neural network.

Science.gov (United States)

Tripathi, Vijay; Gupta, Dwijendra Kumar

2014-01-01

This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

Analysis of plasmid genes by phylogenetic profiling and visualization of homology relationships using Blast2Network

Directory of Open Access Journals (Sweden)

Bazzicalupo Marco

2008-12-01

Full Text Available Abstract Background Phylogenetic methods are well-established bioinformatic tools for sequence analysis, allowing to describe the non-independencies of sequences because of their common ancestor. However, the evolutionary profiles of bacterial genes are often complicated by hidden paralogy and extensive and/or (multiple horizontal gene transfer (HGT events which make bifurcating trees often inappropriate. In this context, plasmid sequences are paradigms of network-like relationships characterizing the evolution of prokaryotes. Actually, they can be transferred among different organisms allowing the dissemination of novel functions, thus playing a pivotal role in prokaryotic evolution. However, the study of their evolutionary dynamics is complicated by the absence of universally shared genes, a prerequisite for phylogenetic analyses. Results To overcome such limitations we developed a bioinformatic package, named Blast2Network (B2N, allowing the automatic phylogenetic profiling and the visualization of homology relationships in a large number of plasmid sequences. The software was applied to the study of 47 completely sequenced plasmids coming from Escherichia, Salmonella and Shigella spps. Conclusion The tools implemented by B2N allow to describe and visualize in a new way some of the evolutionary features of plasmid molecules of Enterobacteriaceae; in particular it helped to shed some light on the complex history of Escherichia, Salmonella and Shigella plasmids and to focus on possible roles of unannotated proteins. The proposed methodology is general enough to be used for comparative genomic analyses of bacteria.

A neural network approach to discrimination between defects and calyces in oranges

Directory of Open Access Journals (Sweden)

Salvatore Ingrassia

1993-11-01

Full Text Available The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the discriminant function is designed by means of a neural network on the basis of a suitable vector representation of the images. Numerical experiments give 5 misclassifications in a set of 52 images, where only three defects have been classified as calyces.

Indoor location system based on discriminant-adaptive neural network in IEEE 802.11 environments.

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Fang, Shih-Hau; Lin, Tsung-Nan

2008-11-01

This brief paper presents a novel localization algorithm, named discriminant-adaptive neural network (DANN), which takes the received signal strength (RSS) from the access points (APs) as inputs to infer the client position in the wireless local area network (LAN) environment. We extract the useful information into discriminative components (DCs) for network learning. The nonlinear relationship between RSS and the position is then accurately constructed by incrementally inserting the DCs and recursively updating the weightings in the network until no further improvement is required. Our localization system is developed in a real-world wireless LAN WLAN environment, where the realistic RSS measurement is collected. We implement the traditional approaches on the same test bed, including weighted kappa-nearest neighbor (WKNN), maximum likelihood (ML), and multilayer perceptron (MLP), and compare the results. The experimental results indicate that the proposed algorithm is much higher in accuracy compared with other examined techniques. The improvement can be attributed to that only the useful information is efficiently extracted for positioning while the redundant information is regarded as noise and discarded. Finally, the analysis shows that our network intelligently accomplishes learning while the inserted DCs provide sufficient information.

Microbial network, phylogenetic diversity and community membership in the active layer across a permafrost thaw gradient.

Science.gov (United States)

Mondav, Rhiannon; McCalley, Carmody K; Hodgkins, Suzanne B; Frolking, Steve; Saleska, Scott R; Rich, Virginia I; Chanton, Jeff P; Crill, Patrick M

2017-08-01

Biogenic production and release of methane (CH 4 ) from thawing permafrost has the potential to be a strong source of radiative forcing. We investigated changes in the active layer microbial community of three sites representative of distinct permafrost thaw stages at a palsa mire in northern Sweden. The palsa site (intact permafrost and low radiative forcing signature) had a phylogenetically clustered community dominated by Acidobacteria and Proteobacteria. The bog (thawing permafrost and low radiative forcing signature) had lower alpha diversity and midrange phylogenetic clustering, characteristic of ecosystem disturbance affecting habitat filtering. Hydrogenotrophic methanogens and Acidobacteria dominated the bog shifting from palsa-like to fen-like at the waterline. The fen (no underlying permafrost, high radiative forcing signature) had the highest alpha, beta and phylogenetic diversity, was dominated by Proteobacteria and Euryarchaeota and was significantly enriched in methanogens. The Mire microbial network was modular with module cores consisting of clusters of Acidobacteria, Euryarchaeota or Xanthomonodales. Loss of underlying permafrost with associated hydrological shifts correlated to changes in microbial composition, alpha, beta and phylogenetic diversity associated with a higher radiative forcing signature. These results support the complex role of microbial interactions in mediating carbon budget changes and climate feedback in response to climate forcing. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

The self-nonself discrimination and the nature and acquisition of the antibody repertoire.

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Coutinho, A

1980-01-01

Network ideas are confronted with current hypotheses for the origin of antibody diversity and self-nonself discrimination. The difficulties of reconciling the promethean evolution of the antibody system with "germ line" theories are discussed, as well as the problems of "somatic" hypotheses to explain the completeness of the antibody repertoire. The formal incompatibility of the network theory with ideas basing self-nonself discrimination on the elimination of self-reactive cells is demonstrated, as well as the difficulties of these and other environment-dependent hypotheses for lymphocyte activation, to encompass the internal activity in the immune system. It is argued, on the other hand, that the limitations of the network theory in providing a functional basis for the idiotypic network and in accounting for self-nonself discrimination, can be solved by finding in a complete repertoire of antibody-combining sites the complementary structures to growth receptors on B lymphocytes, and by using these as internal mitogens in the expansion of the precursor cell pools and in the maintenance of the mature steady states. Letting self-nonself discrimination be accounted for by such growth receptors, both the integrity of the antibody repertoire and the internal activity in the system can also be ensured. Moreover, by postulating a germ line origin for the antireceptor antibodies and by accepting idiotypic cross-reactivity between growth receptors and other germ line antibodies, the possibilities are set for a phylogenetically and ontogenically autonomous immune system embodied with the capabilities for self-expansion, diversification and selection of available repertoires. Its promethean characteristics are explained by its completeness, and this is achieved by idiotypic interactions between growth receptors and a limited number of complementary or cross-reactive germ line antibodies, naturally selected on the basis of their structural relationships with growth receptors.

Subsidence feature discrimination using deep convolutional neral networks in synthetic aperture radar imagery

CSIR Research Space (South Africa)

Schwegmann, Colin P

2017-07-01

Full Text Available International Geoscience and Remote Sensing Symposium (IGARSS), 23-28 July 2017, Fort Worth, TX, USA SUBSIDENCE FEATURE DISCRIMINATION USING DEEP CONVOLUTIONAL NEURAL NETWORKS IN SYNTHETIC APERTURE RADAR IMAGERY Schwegmann, Colin P Kleynhans, Waldo...

Synthetic aperture radar ship discrimination, generation and latent variable extraction using information maximizing generative adversarial networks

CSIR Research Space (South Africa)

Schwegmann, Colin P

2017-07-01

Full Text Available such as Synthetic Aperture Radar imagery. To aid in the creation of improved machine learning-based ship detection and discrimination methods this paper applies a type of neural network known as an Information Maximizing Generative Adversarial Network. Generative...

Novel Strategy for Discrimination of Transcription Factor Binding Motifs Employing Mathematical Neural Network

Science.gov (United States)

Sugimoto, Asuka; Sumi, Takuya; Kang, Jiyoung; Tateno, Masaru

2017-07-01

Recognition in biological macromolecular systems, such as DNA-protein recognition, is one of the most crucial problems to solve toward understanding the fundamental mechanisms of various biological processes. Since specific base sequences of genome DNA are discriminated by proteins, such as transcription factors (TFs), finding TF binding motifs (TFBMs) in whole genome DNA sequences is currently a central issue in interdisciplinary biophysical and information sciences. In the present study, a novel strategy to create a discriminant function for discrimination of TFBMs by constituting mathematical neural networks (NNs) is proposed, together with a method to determine the boundary of signals (TFBMs) and noise in the NN-score (output) space. This analysis also leads to the mathematical limitation of discrimination in the recognition of features representing TFBMs, in an information geometrical manifold. Thus, the present strategy enables the identification of the whole space of TFBMs, right up to the noise boundary.

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

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Fountain-Jones, Nicholas M; Packer, Craig; Troyer, Jennifer L; VanderWaal, Kimberly; Robinson, Stacie; Jacquot, Maude; Craft, Meggan E

2017-10-01

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIV Ple ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIV Ple molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIV Ple co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIV Ple network. While social organization (i.e., pride) was an important component of FIV Ple transmission pathways at all scales, we find that FIV Ple subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIV Ple transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

The neural network involved in a bimanual tactile-tactile matching discrimination task: a functional imaging study at 3 T

Energy Technology Data Exchange (ETDEWEB)

Habas, Christophe; Cabanis, Emmanuel A. [UPMC Paris 6, Service de NeuroImagerie, Hopital des Quinze-Vingts, Paris (France)

2007-08-15

The cerebral and cerebellar network involved in a bimanual object recognition was studied in blood oxygenation dependent level functional magnetic resonance imaging (fMRI). Nine healthy right-handed volunteers were scanned (1) while performing bilateral finger movements (nondiscrimination motor task), and (2) while performing a bimanual tactile-tactile matching discrimination task using small chess pieces (tactile discrimination task). Extensive activations were specifically observed in the parietal (SII, superior lateral lobule), insular, prefrontal, cingulate and neocerebellar cortices (HVIII), with a left predominance in motor areas, during the tactile discrimination task in contrast to the findings during the nondiscrimination motor task. Bimanual tactile-tactile matching discrimination recruits multiple sensorimotor and associative cerebral and neocerebellar networks (including the cerebellar second homunculus, HVIII), comparable to the neural circuits involved in unimanual tactile object recognition. (orig.)

Phylogenetic congruence between subtropical trees and their associated fungi

NARCIS (Netherlands)

Liu, Xubing; Liang, Minxia; Etienne, Rampal S.; Gilbert, Gregory S; Yu, Shixiao

2016-01-01

Recent studies have detected phylogenetic signals in pathogen-host networks for both soil-borne and leaf-infecting fungi, suggesting that pathogenic fungi may track or coevolve with their preferred hosts. However, a phylogenetically concordant relationship between multiple hosts and multiple fungi

Neural Network Aided Glitch-Burst Discrimination and Glitch Classification

Science.gov (United States)

Rampone, Salvatore; Pierro, Vincenzo; Troiano, Luigi; Pinto, Innocenzo M.

2013-11-01

We investigate the potential of neural-network based classifiers for discriminating gravitational wave bursts (GWBs) of a given canonical family (e.g. core-collapse supernova waveforms) from typical transient instrumental artifacts (glitches), in the data of a single detector. The further classification of glitches into typical sets is explored. In order to provide a proof of concept, we use the core-collapse supernova waveform catalog produced by H. Dimmelmeier and co-Workers, and the data base of glitches observed in laser interferometer gravitational wave observatory (LIGO) data maintained by P. Saulson and co-Workers to construct datasets of (windowed) transient waveforms (glitches and bursts) in additive (Gaussian and compound-Gaussian) noise with different signal-to-noise ratios (SNR). Principal component analysis (PCA) is next implemented for reducing data dimensionality, yielding results consistent with, and extending those in the literature. Then, a multilayer perceptron is trained by a backpropagation algorithm (MLP-BP) on a data subset, and used to classify the transients as glitch or burst. A Self-Organizing Map (SOM) architecture is finally used to classify the glitches. The glitch/burst discrimination and glitch classification abilities are gauged in terms of the related truth tables. Preliminary results suggest that the approach is effective and robust throughout the SNR range of practical interest. Perspective applications pertain both to distributed (network, multisensor) detection of GWBs, where some intelligence at the single node level can be introduced, and instrument diagnostics/optimization, where spurious transients can be identified, classified and hopefully traced back to their entry points.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

Science.gov (United States)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

International Nuclear Information System (INIS)

Hosseini-Golgoo, S M; Bozorgi, H; Saberkari, A

2015-01-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively. (paper)

Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

International Nuclear Information System (INIS)

Hooman, A.; Mohammadzadeh, M.

2008-01-01

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curve (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions

Limited overlap between phylogenetic HIV and hepatitis C virus clusters illustrates the dynamic sexual network structure of Dutch HIV-infected MSM.

Science.gov (United States)

Vanhommerig, Joost W; Bezemer, Daniela; Molenkamp, Richard; Van Sighem, Ard I; Smit, Colette; Arends, Joop E; Lauw, Fanny N; Brinkman, Kees; Rijnders, Bart J; Newsum, Astrid M; Bruisten, Sylvia M; Prins, Maria; Van Der Meer, Jan T; Van De Laar, Thijs J; Schinkel, Janke

2017-09-24

MSM are at increased risk for infection with HIV-1 and hepatitis C virus (HCV). Is HIV/HCV coinfection confined to specific HIV transmission networks? A HIV phylogenetic tree was constructed for 5038 HIV-1 subtype B polymerase (pol) sequences obtained from MSM in the AIDS therapy evaluation in the Netherlands cohort. We investigated the existence of HIV clusters with increased HCV prevalence, the HIV phylogenetic density (i.e. the number of potential HIV transmission partners) of HIV/HCV-coinfected MSM compared with HIV-infected MSM without HCV, and the overlap in HIV and HCV phylogenies using HCV nonstructural protein 5B sequences from 183 HIV-infected MSM with acute HCV infection. Five hundred and sixty-three of 5038 (11.2%) HIV-infected MSM tested HCV positive. Phylogenetic analysis revealed 93 large HIV clusters (≥10 MSM), 370 small HIV clusters (2-9 MSM), and 867 singletons with a median HCV prevalence of 11.5, 11.6, and 9.3%, respectively. We identified six large HIV clusters with elevated HCV prevalence (range 23.5-46.2%). Median HIV phylogenetic densities for MSM with HCV (3, interquartile range 1-7) and without HCV (3, interquartile range 1-8) were similar. HCV phylogeny showed 12 MSM-specific HCV clusters (clustersize: 2-39 HCV sequences); 12.7% of HCV infections were part of the same HIV and HCV cluster. We observed few HIV clusters with elevated HCV prevalence, no increase in the HIV phylogenetic density of HIV/HCV-coinfected MSM compared to HIV-infected MSM without HCV, and limited overlap between HIV and HCV phylogenies among HIV/HCV-coinfected MSM. Our data do not support the existence of MSM-specific sexual networks that fuel both the HIV and HCV epidemic.

On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks

OpenAIRE

Bryant, Christopher; Fischer, Mareike; Linz, Simone; Semple, Charles

2015-01-01

Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe evolution accurately. For instance, processes like hybridization or lateral gene transfer that are commonplace in many groups of organisms and result in mosaic patterns of relationships cannot be represented by a single phylogenetic tree. This is why phylogene...

Phylogenetic Inference of HIV Transmission Clusters

Directory of Open Access Journals (Sweden)

Vlad Novitsky

2017-10-01

Full Text Available Better understanding the structure and dynamics of HIV transmission networks is essential for designing the most efficient interventions to prevent new HIV transmissions, and ultimately for gaining control of the HIV epidemic. The inference of phylogenetic relationships and the interpretation of results rely on the definition of the HIV transmission cluster. The definition of the HIV cluster is complex and dependent on multiple factors, including the design of sampling, accuracy of sequencing, precision of sequence alignment, evolutionary models, the phylogenetic method of inference, and specified thresholds for cluster support. While the majority of studies focus on clusters, non-clustered cases could also be highly informative. A new dimension in the analysis of the global and local HIV epidemics is the concept of phylogenetically distinct HIV sub-epidemics. The identification of active HIV sub-epidemics reveals spreading viral lineages and may help in the design of targeted interventions.HIVclustering can also be affected by sampling density. Obtaining a proper sampling density may increase statistical power and reduce sampling bias, so sampling density should be taken into account in study design and in interpretation of phylogenetic results. Finally, recent advances in long-range genotyping may enable more accurate inference of HIV transmission networks. If performed in real time, it could both inform public-health strategies and be clinically relevant (e.g., drug-resistance testing.

Combustion monitoring of a water tube boiler using a discriminant radial basis network.

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Sujatha, K; Pappa, N

2011-01-01

This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Discrimination Analysis of Earthquakes and Man-Made Events Using ARMA Coefficients Determination by Artificial Neural Networks

International Nuclear Information System (INIS)

AllamehZadeh, Mostafa

2011-01-01

A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neural system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0–6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.

Discrimination Analysis of Earthquakes and Man-Made Events Using ARMA Coefficients Determination by Artificial Neural Networks

Energy Technology Data Exchange (ETDEWEB)

AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com [International Institute of Earthquake Engineering and Seismology (Iran, Islamic Republic of)

2011-12-15

A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neural system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.

The Fair Proportion is a Shapley Value on phylogenetic networks too

OpenAIRE

Coronado, Tomás M.; Riera, Gabriel; Rosselló, Francesc

2018-01-01

The Fair Proportion of a species in a phylogenetic tree is a very simple measure that has been used to assess its value relative to the overall phylogenetic diversity represented by the tree. It has recently been proved by Fuchs and Jin to be equal to the Shapley Value of the coallitional game that sends each subset of species to its rooted Phylogenetic Diversity in the tree. We prove in this paper that this result extends to the natural translations of the Fair Proportion and the rooted Phyl...

Discriminative analysis of early Alzheimer's disease based on two intrinsically anti-correlated networks with resting-state fMRI.

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Wang, Kun; Jiang, Tianzi; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Liu, Zhening

2006-01-01

In this work, we proposed a discriminative model of Alzheimer's disease (AD) on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model used the correlation/anti-correlation coefficients of two intrinsically anti-correlated networks in resting brains, which have been suggested by two recent studies, as the feature of classification. Pseudo-Fisher Linear Discriminative Analysis (pFLDA) was then performed on the feature space and a linear classifier was generated. Using leave-one-out (LOO) cross validation, our results showed a correct classification rate of 83%. We also compared the proposed model with another one based on the whole brain functional connectivity. Our proposed model outperformed the other one significantly, and this implied that the two intrinsically anti-correlated networks may be a more susceptible part of the whole brain network in the early stage of AD.

Discrimination of panti p → tanti t events by a neural network classifier

International Nuclear Information System (INIS)

Cherubini, A.; Odorico, R.

1992-01-01

Neural network and conventional statistical techniques are compared in the problem of discriminating panti p→tanti t events, with top quarks decaying into anything, from the associated hadronic background at the energy of the Fermilab collider. The NN we develop for this sake is an improved version of Kohonen's learning vector quantization scheme. Performance of the NN as a tanti t event classifier is found to be less satisfactory than that achievable by statistical methods. We conclude that the probable reasons for that are: i) The NN approach presents advantages only when dealing with event distributions in the feature space which substantially differ from Gaussians; ii) NN's require much larger training sets of events than statistical discrimination in order to give comparable results. (orig.)

Discrimination between earthquakes and chemical explosions using artificial neural networks

International Nuclear Information System (INIS)

Kundu, Ajit; Bhadauria, Y.S.; Roy, Falguni

2012-05-01

An Artificial Neural Network (ANN) for discriminating between earthquakes and chemical explosions located at epicentral distances, Δ <5 deg from Gauribidanur Array (GBA) has been developed using the short period digital seismograms recorded at GBA. For training the ANN spectral amplitude ratios between P and Lg phases computed at 13 different frequencies in the frequency range of 2-8 Hz, corresponding to 20 earthquakes and 23 chemical explosions were used along with other parameters like magnitude, epicentral distance and amplitude ratios Rg/P and Rg/Lg. After training and development, the ANN has correctly identified a set of 21 test events, comprising 6 earthquakes and 15 chemical explosions. (author)

Phylogenetic congruence between subtropical trees and their associated fungi.

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Liu, Xubing; Liang, Minxia; Etienne, Rampal S; Gilbert, Gregory S; Yu, Shixiao

2016-12-01

Recent studies have detected phylogenetic signals in pathogen-host networks for both soil-borne and leaf-infecting fungi, suggesting that pathogenic fungi may track or coevolve with their preferred hosts. However, a phylogenetically concordant relationship between multiple hosts and multiple fungi in has rarely been investigated. Using next-generation high-throughput DNA sequencing techniques, we analyzed fungal taxa associated with diseased leaves, rotten seeds, and infected seedlings of subtropical trees. We compared the topologies of the phylogenetic trees of the soil and foliar fungi based on the internal transcribed spacer (ITS) region with the phylogeny of host tree species based on matK , rbcL , atpB, and 5.8S genes. We identified 37 foliar and 103 soil pathogenic fungi belonging to the Ascomycota and Basidiomycota phyla and detected significantly nonrandom host-fungus combinations, which clustered on both the fungus phylogeny and the host phylogeny. The explicit evidence of congruent phylogenies between tree hosts and their potential fungal pathogens suggests either diffuse coevolution among the plant-fungal interaction networks or that the distribution of fungal species tracked spatially associated hosts with phylogenetically conserved traits and habitat preferences. Phylogenetic conservatism in plant-fungal interactions within a local community promotes host and parasite specificity, which is integral to the important role of fungi in promoting species coexistence and maintaining biodiversity of forest communities.

Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

Science.gov (United States)

Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

2013-01-01

This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

Predicting rates of interspecific interaction from phylogenetic trees.

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Nuismer, Scott L; Harmon, Luke J

2015-01-01

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction. © 2014 John Wiley & Sons Ltd/CNRS.

Toward a phylogenetic chronology of ancient Gaulish, Celtic, and Indo-European.

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Forster, Peter; Toth, Alfred

2003-07-22

Indo-European is the largest and best-documented language family in the world, yet the reconstruction of the Indo-European tree, first proposed in 1863, has remained controversial. Complications may include ascertainment bias when choosing the linguistic data, and disregard for the wave model of 1872 when attempting to reconstruct the tree. Essentially analogous problems were solved in evolutionary genetics by DNA sequencing and phylogenetic network methods, respectively. We now adapt these tools to linguistics, and analyze Indo-European language data, focusing on Celtic and in particular on the ancient Celtic language of Gaul (modern France), by using bilingual Gaulish-Latin inscriptions. Our phylogenetic network reveals an early split of Celtic within Indo-European. Interestingly, the next branching event separates Gaulish (Continental Celtic) from the British (Insular Celtic) languages, with Insular Celtic subsequently splitting into Brythonic (Welsh, Breton) and Goidelic (Irish and Scottish Gaelic). Taken together, the network thus suggests that the Celtic language arrived in the British Isles as a single wave (and then differentiated locally), rather than in the traditional two-wave scenario ("P-Celtic" to Britain and "Q-Celtic" to Ireland). The phylogenetic network furthermore permits the estimation of time in analogy to genetics, and we obtain tentative dates for Indo-European at 8100 BC +/- 1,900 years, and for the arrival of Celtic in Britain at 3200 BC +/- 1,500 years. The phylogenetic method is easily executed by hand and promises to be an informative approach for many problems in historical linguistics.

Identification of Tunisian Leishmania spp. by PCR amplification of cysteine proteinase B (cpb) genes and phylogenetic analysis.

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Chaouch, Melek; Fathallah-Mili, Akila; Driss, Mehdi; Lahmadi, Ramzi; Ayari, Chiraz; Guizani, Ikram; Ben Said, Moncef; Benabderrazak, Souha

2013-03-01

Discrimination of the Old World Leishmania parasites is important for diagnosis and epidemiological studies of leishmaniasis. We have developed PCR assays that allow the discrimination between Leishmania major, Leishmania tropica and Leishmania infantum Tunisian species. The identification was performed by a simple PCR targeting cysteine protease B (cpb) gene copies. These PCR can be a routine molecular biology tools for discrimination of Leishmania spp. from different geographical origins and different clinical forms. Our assays can be an informative source for cpb gene studying concerning drug, diagnostics and vaccine research. The PCR products of the cpb gene and the N-acetylglucosamine-1-phosphate transferase (nagt) Leishmania gene were sequenced and aligned. Phylogenetic trees of Leishmania based cpb and nagt sequences are close in topology and present the classic distribution of Leishmania in the Old World. The phylogenetic analysis has enabled the characterization and identification of different strains, using both multicopy (cpb) and single copy (nagt) genes. Indeed, the cpb phylogenetic analysis allowed us to identify the Tunisian Leishmania killicki species, and a group which gathers the least evolved isolates of the Leishmania donovani complex, that was originated from East Africa. This clustering confirms the African origin for the visceralizing species of the L. donovani complex. Copyright © 2012 Elsevier B.V. All rights reserved.

Studying the evolutionary relationships and phylogenetic trees of 21 groups of tRNA sequences based on complex networks.

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Wei, Fangping; Chen, Bowen

2012-03-01

To find out the evolutionary relationships among different tRNA sequences of 21 amino acids, 22 networks are constructed. One is constructed from whole tRNAs, and the other 21 networks are constructed from the tRNAs which carry the same amino acids. A new method is proposed such that the alignment scores of any two amino acids groups are determined by the average degree and the average clustering coefficient of their networks. The anticodon feature of isolated tRNA and the phylogenetic trees of 21 group networks are discussed. We find that some isolated tRNA sequences in 21 networks still connect with other tRNAs outside their group, which reflects the fact that those tRNAs might evolve by intercrossing among these 21 groups. We also find that most anticodons among the same cluster are only one base different in the same sites when S ≥ 70, and they stay in the same rank in the ladder of evolutionary relationships. Those observations seem to agree on that some tRNAs might mutate from the same ancestor sequences based on point mutation mechanisms.

Is invasion success of Australian trees mediated by their native biogeography, phylogenetic history, or both?

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Miller, Joseph T; Hui, Cang; Thornhill, Andrew; Gallien, Laure; Le Roux, Johannes J; Richardson, David M

2016-12-30

For a plant species to become invasive it has to progress along the introduction-naturalization-invasion (INI) continuum which reflects the joint direction of niche breadth. Identification of traits that correlate with and drive species invasiveness along the continuum is a major focus of invasion biology. If invasiveness is underlain by heritable traits, and if such traits are phylogenetically conserved, then we would expect non-native species with different introduction status (i.e. position along the INI continuum) to show phylogenetic signal. This study uses two clades that contain a large number of invasive tree species from the genera Acacia and Eucalyptus to test whether geographic distribution and a novel phylogenetic conservation method can predict which species have been introduced, became naturalized, and invasive. Our results suggest that no underlying phylogenetic signal underlie the introduction status for both groups of trees, except for introduced acacias. The more invasive acacia clade contains invasive species that have smoother geographic distributions and are more marginal in the phylogenetic network. The less invasive eucalyptus group contains invasive species that are more clustered geographically, more centrally located in the phylogenetic network and have phylogenetic distances between invasive and non-invasive species that are trending toward the mean pairwise distance. This suggests that highly invasive groups may be identified because they have invasive species with smoother and faster expanding native distributions and are located more to the edges of phylogenetic networks than less invasive groups. Published by Oxford University Press on behalf of the Annals of Botany Company.

Phylogenetic representativeness: a new method for evaluating taxon sampling in evolutionary studies

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Passamonti Marco

2010-04-01

Full Text Available Abstract Background Taxon sampling is a major concern in phylogenetic studies. Incomplete, biased, or improper taxon sampling can lead to misleading results in reconstructing evolutionary relationships. Several theoretical methods are available to optimize taxon choice in phylogenetic analyses. However, most involve some knowledge about the genetic relationships of the group of interest (i.e., the ingroup, or even a well-established phylogeny itself; these data are not always available in general phylogenetic applications. Results We propose a new method to assess taxon sampling developing Clarke and Warwick statistics. This method aims to measure the "phylogenetic representativeness" of a given sample or set of samples and it is based entirely on the pre-existing available taxonomy of the ingroup, which is commonly known to investigators. Moreover, our method also accounts for instability and discordance in taxonomies. A Python-based script suite, called PhyRe, has been developed to implement all analyses we describe in this paper. Conclusions We show that this method is sensitive and allows direct discrimination between representative and unrepresentative samples. It is also informative about the addition of taxa to improve taxonomic coverage of the ingroup. Provided that the investigators' expertise is mandatory in this field, phylogenetic representativeness makes up an objective touchstone in planning phylogenetic studies.

Cophenetic metrics for phylogenetic trees, after Sokal and Rohlf.

Science.gov (United States)

Cardona, Gabriel; Mir, Arnau; Rosselló, Francesc; Rotger, Lucía; Sánchez, David

2013-01-16

Phylogenetic tree comparison metrics are an important tool in the study of evolution, and hence the definition of such metrics is an interesting problem in phylogenetics. In a paper in Taxon fifty years ago, Sokal and Rohlf proposed to measure quantitatively the difference between a pair of phylogenetic trees by first encoding them by means of their half-matrices of cophenetic values, and then comparing these matrices. This idea has been used several times since then to define dissimilarity measures between phylogenetic trees but, to our knowledge, no proper metric on weighted phylogenetic trees with nested taxa based on this idea has been formally defined and studied yet. Actually, the cophenetic values of pairs of different taxa alone are not enough to single out phylogenetic trees with weighted arcs or nested taxa. For every (rooted) phylogenetic tree T, let its cophenetic vectorφ(T) consist of all pairs of cophenetic values between pairs of taxa in T and all depths of taxa in T. It turns out that these cophenetic vectors single out weighted phylogenetic trees with nested taxa. We then define a family of cophenetic metrics dφ,p by comparing these cophenetic vectors by means of Lp norms, and we study, either analytically or numerically, some of their basic properties: neighbors, diameter, distribution, and their rank correlation with each other and with other metrics. The cophenetic metrics can be safely used on weighted phylogenetic trees with nested taxa and no restriction on degrees, and they can be computed in O(n2) time, where n stands for the number of taxa. The metrics dφ,1 and dφ,2 have positive skewed distributions, and they show a low rank correlation with the Robinson-Foulds metric and the nodal metrics, and a very high correlation with each other and with the splitted nodal metrics. The diameter of dφ,p, for p⩾1 , is in O(n(p+2)/p), and thus for low p they are more discriminative, having a wider range of values.

Principal component and discriminant analyses as powerful tools to support taxonomic identification and their use for functional and phylogenetic signal detection of isolated fossil shark teeth.

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Giuseppe Marramà

Full Text Available Identifying isolated teeth of fossil selachians only based on qualitative characters is sometimes hindered by similarity in their morphology, resulting often in heated taxonomic debates. On the other hand, the use of quantitative characters (i.e. measurements has been often neglected or underestimated in characterization and identification of fossil teeth of selachians. Here we show that, employing a robust methodological protocol based on principal component and discriminant analyses on a sample of 175 isolated fossil teeth of lamniform sharks, the traditional morphometrics can be useful to support and complement the classic taxonomic identification made on qualitative features. Furthermore, we show that discriminant analysis can be successfully useful to assign indeterminate isolated shark teeth to a certain taxon. Finally, the degree of separation of the clusters might be used to predict functional and probably also phylogenetic signals in lamniform shark teeth. However, this needs to be tested in the future employing teeth of more extant and extinct lamniform sharks and it must be pointed out that this approach does not replace in any way the qualitative analysis, but it is intended to complement and support it.

Growth rules based on the modularity of the Canarian Aeonium (Crassulaceae) and their phylogenetic value

DEFF Research Database (Denmark)

Jorgensen, T.H.; Olesen, J.M.

2000-01-01

Growth forms of 22 species of Aeonium (Crassulaceae) were quantified. Since all species are simple in their modular construction, models were developed to predict module length, branching mode and flowering probability using linear and logistic regression. When combined, the parameters...... of these models are species specific. A discriminant analysis generates a statistically significant separation of species at the level of phylogenetic sections. The results therefore demonstrate the phylogenetic value of growth rules in plants. This dynamic approach strongly contrasts with the traditional static...

Label-Driven Learning Framework: Towards More Accurate Bayesian Network Classifiers through Discrimination of High-Confidence Labels

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Yi Sun

2017-12-01

Full Text Available Bayesian network classifiers (BNCs have demonstrated competitive classification accuracy in a variety of real-world applications. However, it is error-prone for BNCs to discriminate among high-confidence labels. To address this issue, we propose the label-driven learning framework, which incorporates instance-based learning and ensemble learning. For each testing instance, high-confidence labels are first selected by a generalist classifier, e.g., the tree-augmented naive Bayes (TAN classifier. Then, by focusing on these labels, conditional mutual information is redefined to more precisely measure mutual dependence between attributes, thus leading to a refined generalist with a more reasonable network structure. To enable finer discrimination, an expert classifier is tailored for each high-confidence label. Finally, the predictions of the refined generalist and the experts are aggregated. We extend TAN to LTAN (Label-driven TAN by applying the proposed framework. Extensive experimental results demonstrate that LTAN delivers superior classification accuracy to not only several state-of-the-art single-structure BNCs but also some established ensemble BNCs at the expense of reasonable computation overhead.

The stochastic network dynamics underlying perceptual discrimination

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Genis Prat-Ortega

2015-04-01

Full Text Available The brain is able to interpret streams of high-dimensional ambiguous information and yield coherent percepts. The mechanisms governing sensory integration have been extensively characterized using time-varying visual stimuli (Britten et al. 1996; Roitman and Shadlen 2002, but some of the basic principles regarding the network dynamics underlying this process remain largely unknown. We captured the basic features of a neural integrator using three canonical one-dimensional models: (1 the Drift Diffusion Model (DDM, (2 the Perfect Integrator (PI which is a particular case of the DDM where the bounds are set to infinity and (3 the double-well potential (DW which captures the dynamics of the attractor networks (Wang 2002; Roxin and Ledberg 2008. Although these models has been widely studied (Bogacz et al. 2006; Roxin and Ledberg 2008; Gold and Shadlen 2002, it has been difficult to experimentally discriminate among them because most of the observables measured are only quantitatively different among these models (e.g. psychometric curves. Here we aim to find experimentally measurable quantities that can yield qualitatively different behaviors depending on the nature of the underlying network dynamics. We examined the categorization dynamics of these models in response to fluctuating stimuli of different duration (T. On each time step, stimuli are drawn from a Gaussian distribution N(μ, σ and the two stimulus categories are defined by μ > 0 and μ < 0. Psychometric curves can therefore be obtained by quantifying the probability of the integrator to yield one category versus μ . We find however that varying σ can reveal more clearly the differences among the different integrators. In the small σ regime, both the DW and the DDM perform transient integration and exhibit a decaying stimulus reverse correlation kernel revealing a primacy effect (Nienborg and Cumming 2009; Wimmer et al. 2015 . In the large σ regime, the integration in the DDM

Unrealistic phylogenetic trees may improve phylogenetic footprinting.

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Nettling, Martin; Treutler, Hendrik; Cerquides, Jesus; Grosse, Ivo

2017-06-01

The computational investigation of DNA binding motifs from binding sites is one of the classic tasks in bioinformatics and a prerequisite for understanding gene regulation as a whole. Due to the development of sequencing technologies and the increasing number of available genomes, approaches based on phylogenetic footprinting become increasingly attractive. Phylogenetic footprinting requires phylogenetic trees with attached substitution probabilities for quantifying the evolution of binding sites, but these trees and substitution probabilities are typically not known and cannot be estimated easily. Here, we investigate the influence of phylogenetic trees with different substitution probabilities on the classification performance of phylogenetic footprinting using synthetic and real data. For synthetic data we find that the classification performance is highest when the substitution probability used for phylogenetic footprinting is similar to that used for data generation. For real data, however, we typically find that the classification performance of phylogenetic footprinting surprisingly increases with increasing substitution probabilities and is often highest for unrealistically high substitution probabilities close to one. This finding suggests that choosing realistic model assumptions might not always yield optimal predictions in general and that choosing unrealistically high substitution probabilities close to one might actually improve the classification performance of phylogenetic footprinting. The proposed PF is implemented in JAVA and can be downloaded from https://github.com/mgledi/PhyFoo. : martin.nettling@informatik.uni-halle.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Complex networks from experimental horizontal oil–water flows: Community structure detection versus flow pattern discrimination

International Nuclear Information System (INIS)

Gao, Zhong-Ke; Fang, Peng-Cheng; Ding, Mei-Shuang; Yang, Dan; Jin, Ning-De

2015-01-01

We propose a complex network-based method to distinguish complex patterns arising from experimental horizontal oil–water two-phase flow. We first use the adaptive optimal kernel time–frequency representation (AOK TFR) to characterize flow pattern behaviors from the energy and frequency point of view. Then, we infer two-phase flow complex networks from experimental measurements and detect the community structures associated with flow patterns. The results suggest that the community detection in two-phase flow complex network allows objectively discriminating complex horizontal oil–water flow patterns, especially for the segregated and dispersed flow patterns, a task that existing method based on AOK TFR fails to work. - Highlights: • We combine time–frequency analysis and complex network to identify flow patterns. • We explore the transitional flow behaviors in terms of betweenness centrality. • Our analysis provides a novel way for recognizing complex flow patterns. • Broader applicability of our method is demonstrated and articulated

Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters

NARCIS (Netherlands)

Iersel, van L.J.J.; Kelk, S.M.; Rupp, R.; Huson, D.H.

2010-01-01

Phylogenetic trees are widely used to display estimates of how groups of species are evolved. Each phylogenetic tree can be seen as a collection of clusters, subgroups of the species that evolved from a common ancestor. When phylogenetic trees are obtained for several datasets (e.g. for different

Phylogenetic trees

OpenAIRE

Baños, Hector; Bushek, Nathaniel; Davidson, Ruth; Gross, Elizabeth; Harris, Pamela E.; Krone, Robert; Long, Colby; Stewart, Allen; Walker, Robert

2016-01-01

We introduce the package PhylogeneticTrees for Macaulay2 which allows users to compute phylogenetic invariants for group-based tree models. We provide some background information on phylogenetic algebraic geometry and show how the package PhylogeneticTrees can be used to calculate a generating set for a phylogenetic ideal as well as a lower bound for its dimension. Finally, we show how methods within the package can be used to compute a generating set for the join of any two ideals.

Stigma, discrimination, empowerment and social networks: a preliminary investigation of their influence on subjective quality of life in a Swedish sample.

Science.gov (United States)

Lundberg, Bertil; Hansson, Lars; Wentz, Elisabet; Björkman, Tommy

2008-01-01

Studies investigating the importance of social network, empowerment and experiences of stigma on subjective quality of life among persons with mental illness are rare. This study aimed to investigate beliefs of devaluation/discrimination, actual rejection experiences, empowerment, social network and the relationship of these factors to subjective quality of life among subjects with mental illness. A cross-sectional study assessing beliefs of devaluation/discrimination, actual rejection experiences, empowerment, social network and subjective quality of life was performed on 150 subjects with mental illness. The factors most prominently related to subjective quality of life were overall empowerment and overall social network. For a subgroup of subjects suffering from psychotic disorders there was a significant negative relationship between subjective quality of life and rejection experiences. This group also reported more frequent rejection experiences. The findings indicate that persons with mental illness are a heterogeneous group with regard to the influence of social network, stigma and empowerment on subjective quality of life. The negative impact of actual rejection experiences might express that, in order to increase subjective quality of life, stigma must be addressed as a separate and important factor in its own right.

Maximizing the phylogenetic diversity of seed banks.

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Griffiths, Kate E; Balding, Sharon T; Dickie, John B; Lewis, Gwilym P; Pearce, Tim R; Grenyer, Richard

2015-04-01

Ex situ conservation efforts such as those of zoos, botanical gardens, and seed banks will form a vital complement to in situ conservation actions over the coming decades. It is therefore necessary to pay the same attention to the biological diversity represented in ex situ conservation facilities as is often paid to protected-area networks. Building the phylogenetic diversity of ex situ collections will strengthen our capacity to respond to biodiversity loss. Since 2000, the Millennium Seed Bank Partnership has banked seed from 14% of the world's plant species. We assessed the taxonomic, geographic, and phylogenetic diversity of the Millennium Seed Bank collection of legumes (Leguminosae). We compared the collection with all known legume genera, their known geographic range (at country and regional levels), and a genus-level phylogeny of the legume family constructed for this study. Over half the phylogenetic diversity of legumes at the genus level was represented in the Millennium Seed Bank. However, pragmatic prioritization of species of economic importance and endangerment has led to the banking of a less-than-optimal phylogenetic diversity and prioritization of range-restricted species risks an underdispersed collection. The current state of the phylogenetic diversity of legumes in the Millennium Seed Bank could be substantially improved through the strategic banking of relatively few additional taxa. Our method draws on tools that are widely applied to in situ conservation planning, and it can be used to evaluate and improve the phylogenetic diversity of ex situ collections. © 2014 Society for Conservation Biology.

The performance of phylogenetic algorithms in estimating haplotype genealogies with migration.

Science.gov (United States)

Salzburger, Walter; Ewing, Greg B; Von Haeseler, Arndt

2011-05-01

Genealogies estimated from haplotypic genetic data play a prominent role in various biological disciplines in general and in phylogenetics, population genetics and phylogeography in particular. Several software packages have specifically been developed for the purpose of reconstructing genealogies from closely related, and hence, highly similar haplotype sequence data. Here, we use simulated data sets to test the performance of traditional phylogenetic algorithms, neighbour-joining, maximum parsimony and maximum likelihood in estimating genealogies from nonrecombining haplotypic genetic data. We demonstrate that these methods are suitable for constructing genealogies from sets of closely related DNA sequences with or without migration. As genealogies based on phylogenetic reconstructions are fully resolved, but not necessarily bifurcating, and without reticulations, these approaches outperform widespread 'network' constructing methods. In our simulations of coalescent scenarios involving panmictic, symmetric and asymmetric migration, we found that phylogenetic reconstruction methods performed well, while the statistical parsimony approach as implemented in TCS performed poorly. Overall, parsimony as implemented in the PHYLIP package performed slightly better than other methods. We further point out that we are not making the case that widespread 'network' constructing methods are bad, but that traditional phylogenetic tree finding methods are applicable to haplotypic data and exhibit reasonable performance with respect to accuracy and robustness. We also discuss some of the problems of converting a tree to a haplotype genealogy, in particular that it is nonunique. © 2011 Blackwell Publishing Ltd.

Search for the standard model Higgs boson in $e^{+}e^{-}$ four- jet topology using neural networks and discriminant analysis

CERN Document Server

Mjahed, M

2003-01-01

We present an attempt to separate between Higgs boson events (e/sup + /e/sup -/ to ZH to qqbb) and other physics processes in the 4-jet channel (e/sup +/e/sup -/ to Z/ gamma , W/sup +/W, ZZ to 4jets), using the discriminant analysis and neural networks methods. Events were produced at LEP2 energies, using the Lund Monte Carlo generator and the Aleph package. The most discriminant variables as the reconstructed jet mass, the jet properties (b-tag, rapidity weighted moments) and other variables are used. (8 refs).

Incompletely resolved phylogenetic trees inflate estimates of phylogenetic conservatism.

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Davies, T Jonathan; Kraft, Nathan J B; Salamin, Nicolas; Wolkovich, Elizabeth M

2012-02-01

The tendency for more closely related species to share similar traits and ecological strategies can be explained by their longer shared evolutionary histories and represents phylogenetic conservatism. How strongly species traits co-vary with phylogeny can significantly impact how we analyze cross-species data and can influence our interpretation of assembly rules in the rapidly expanding field of community phylogenetics. Phylogenetic conservatism is typically quantified by analyzing the distribution of species values on the phylogenetic tree that connects them. Many phylogenetic approaches, however, assume a completely sampled phylogeny: while we have good estimates of deeper phylogenetic relationships for many species-rich groups, such as birds and flowering plants, we often lack information on more recent interspecific relationships (i.e., within a genus). A common solution has been to represent these relationships as polytomies on trees using taxonomy as a guide. Here we show that such trees can dramatically inflate estimates of phylogenetic conservatism quantified using S. P. Blomberg et al.'s K statistic. Using simulations, we show that even randomly generated traits can appear to be phylogenetically conserved on poorly resolved trees. We provide a simple rarefaction-based solution that can reliably retrieve unbiased estimates of K, and we illustrate our method using data on first flowering times from Thoreau's woods (Concord, Massachusetts, USA).

Discriminative Relational Topic Models.

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Chen, Ning; Zhu, Jun; Xia, Fei; Zhang, Bo

2015-05-01

Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance.

Incorporating phylogenetic information for the definition of floristic districts in hyperdiverse Amazon forests: Implications for conservation

OpenAIRE

Guevara Andino, Juan Ernesto; Pitman, Nigel C. A.; ter Steege, Hans; Mogollón, Hugo; Ceron, Carlos; Palacios, Walter; Oleas, Nora; Fine, Paul V. A.

2017-01-01

Abstract Using complementary metrics to evaluate phylogenetic diversity can facilitate the delimitation of floristic units and conservation priority areas. In this study, we describe the spatial patterns of phylogenetic alpha and beta diversity, phylogenetic endemism, and evolutionary distinctiveness of the hyperdiverse Ecuador Amazon forests and define priority areas for conservation. We established a network of 62 one‐hectare plots in terra firme forests of Ecuadorian Amazon. In these plots...

Application of artificial intelligence to electrofacies identification: neural networks versus discriminant analysis; Aplicacao de inteligencia artificial na identificacao de eletrofacies redes neuroniais versus analise discriminante

Energy Technology Data Exchange (ETDEWEB)

Silva Rodrigues, F da [PETROBRAS, Rio de Janeiro, RJ (Brazil); Queiroz Neto, I.A. de [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas

1992-07-01

Electro-facies are identified by neural network trained with well log and core data. Differences between neural network and expert system are discussed. According the author, the combination of neural network computing and traditional computing methods, like discriminant analysis, can help in the solution of many problems in electro-facies identification. 5 figs., 1 tab., 11 refs.

Cosmic ray antiproton/electron discrimination capability of the CAPRICE silicon-tungsten calorimeter using neural networks

International Nuclear Information System (INIS)

Bellotti, R.; Boezio, M.; Castellano, M.; De Marzo, C.; Picozza, P.; Prigiobbe, V.; Sparvoli, R.; Tirocchi, M.

1996-01-01

A data analysis based on an artificial neural network classifier is proposed to identify cosmic ray antiprotons detected with the CAPRICE silicon-tungsten imaging calorimeter against electron background in the energy range 1.2-4.0 GeV. A set of new physical variables, describing the events inside the calorimeter on the base of their different patterns, are introduced in order to discriminate between hadronic and electromagnetic showers. The ability of the artificial neural network classifier to perform a careful multidimensional analysis gives the possibility to identify antiprotons with an electron rejection 408±85 (stat) at 95.0±0.2 (stat)% of signal detection efficiency. The high accuracy achieved by this method improves substantially the efficiency in the evaluation of the cosmic ray antiproton spectrum. (orig.)

Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales.

Science.gov (United States)

Purschke, Oliver; Michalski, Stefan G; Bruelheide, Helge; Durka, Walter

2017-12-01

Although spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scales, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic turnover across phylogenetic scales, accounting for covariation with environmental differences. We compared phylogenetic turnover, at the species- and individual-level, within and between five successional stages, representing woody plant communities in a subtropical forest chronosequence. We decomposed turnover at different phylogenetic depths and assessed its covariation with between-plot abiotic differences. Phylogenetic turnover between stages was low relative to species turnover and was not explained by abiotic differences. However, within the late-successional stages, there was high presence-/absence-based turnover (clustering) that occurred deep in the phylogeny and covaried with environmental differentiation. Our results support a deterministic model of community assembly where (i) phylogenetic composition is constrained through successional time, but (ii) toward late succession, species sorting into preferred habitats according to niche traits that are conserved deep in phylogeny, becomes increasingly important.

Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

Directory of Open Access Journals (Sweden)

Ana-Isabel de Castro

2012-01-01

Full Text Available In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC analysis and two neural networks, specifically, multilayer perceptron (MLP and radial basis function (RBF. Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops.

Perceived ethnic discrimination and depressive symptoms: the buffering effects of ethnic identity, religion and ethnic social network.

Science.gov (United States)

Ikram, Umar Z; Snijder, Marieke B; de Wit, Matty A S; Schene, Aart H; Stronks, Karien; Kunst, Anton E

2016-05-01

Perceived ethnic discrimination (PED) is positively associated with depressive symptoms in ethnic minority groups in Western countries. Psychosocial factors may buffer against the health impact of PED, but evidence is lacking from Europe. We assessed whether ethnic identity, religion, and ethnic social network act as buffers in different ethnic minority groups in Amsterdam, the Netherlands. Baseline data were used from the HEalthy Living In a Urban Setting study collected from January 2011 to June 2014. The random sample included 2501 South-Asian Surinamese, 2292 African Surinamese, 1877 Ghanaians, 2626 Turks, and 2484 Moroccans aged 18-70 years. Depressive symptoms were assessed using the Patient Health Questionnaire-9. PED was measured with the Everyday Discrimination Scale. Ethnic identity was assessed using the Psychological Acculturation Scale. Practicing religion was determined. Ethnic social network was assessed with the number of same-ethnic friends and amount of leisure time spent with same-ethnic people. PED was positively associated with depressive symptoms in all groups. The association was weaker among (a) those with strong ethnic identity in African Surinamese and Ghanaians, (b) those practicing religion among African Surinamese and Moroccans, (c) those with many same-ethnic friends in South-Asian Surinamese, Ghanaians, and Turks, and (d) those who spend leisure time with same-ethnic people among African Surinamese and Turks. Ethnic identity, religion, and ethnic social network weakened the association between PED and depressive symptoms, but the effects differed by ethnic minority group. These findings suggest that ethnic minority groups employ different resources to cope with PED.

Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

Science.gov (United States)

Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh

2014-05-01

Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Determination of the isotopic (C-13/C-12) discrimination by terrestrial biology from a global network of observations

International Nuclear Information System (INIS)

Bakwin, P.S.; Tans, P.P.; White, J.W.C.; Andres, R.J.

1998-01-01

Data from the National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory global air sampling network are analysed in order to extract the signatures of isotopic (C-13/C-12) discrimination by the terrestrial iota and of fossil fuel combustion for the regions surrounding the sampling sites. Measurements of carbon monoxide (CO) are used to give an estimate of the contribution of fossil fuel combustion to the short-term variability of carbon dioxide. In general, variations of CO 2 are more strongly dominated by biological exchange, so the isotopic signature of fossil fuel combustion, while consistent with inventory estimates, is not well constrained by the observations. Conversely, results for isotope discrimination by the terrestrial biosphere are not strongly dependent on assumptions about fossil fuel combustion. The analysis appears valid primarily for stations fairly near continental source/sink regions, particularly for midlatitude regions of the northern hemisphere. For these stations a mean discrimination of -16.8 per mil (%) is derived, with site-to-site variability of 0.8% and with little or no consistent latitudinal gradient

Phylogenetic investigation of a statewide HIV-1 epidemic reveals ongoing and active transmission networks among men who have sex with men

Science.gov (United States)

Chan, Philip A.; Hogan, Joseph W.; Huang, Austin; DeLong, Allison; Salemi, Marco; Mayer, Kenneth H.; Kantor, Rami

2015-01-01

Background Molecular epidemiologic evaluation of HIV-1 transmission networks can elucidate behavioral components of transmission that can be targets for intervention. Methods We combined phylogenetic and statistical approaches using pol sequences from patients diagnosed 2004-2011 at a large HIV center in Rhode Island, following 75% of the state’s HIV population. Phylogenetic trees were constructed using maximum likelihood and putative transmission clusters were evaluated using latent class analyses (LCA) to determine association of cluster size with underlying demographic/behavioral characteristics. A logistic growth model was used to assess intra-cluster dynamics over time and predict “active” clusters that were more likely to harbor undiagnosed infections. Results Of 1,166 HIV-1 subtype B sequences, 31% were distributed among 114 statistically-supported, monophyletic clusters (range: 2-15 sequences/cluster). Sequences from men who have sex with men (MSM) formed 52% of clusters. LCA demonstrated that sequences from recently diagnosed (2008-2011) MSM with primary HIV infection (PHI) and other sexually transmitted infections (STIs) were more likely to form larger clusters (Odds Ratio 1.62-11.25, ppornographic stores. Four large clusters with 38 sequences (100% male, 89% MSM) had a high-probability of harboring undiagnosed infections and included younger MSM with PHI and STIs. Conclusions In this first large-scale molecular epidemiologic investigation of HIV-1 transmission in New England, sexual networks among recently diagnosed MSM with PHI and concomitant STIs contributed to ongoing transmission. Characterization of transmission dynamics revealed actively growing clusters which may be targets for intervention. PMID:26258569

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Sandeep [Tata Inst. of Fundamental Research, Bombay (India); Rao, Basuthkar J. [Tata Inst. of Fundamental Research, Bombay (India); Baker, Nathan A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Asgeirsson, Bjarni [Univ. of Iceland, Reykjavik (Iceland)

2013-04-01

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits the MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

Science.gov (United States)

Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Incorporating phylogenetic information for the definition of floristic districts in hyperdiverse Amazon forests: Implications for conservation.

Science.gov (United States)

Guevara Andino, Juan Ernesto; Pitman, Nigel C A; Ter Steege, Hans; Mogollón, Hugo; Ceron, Carlos; Palacios, Walter; Oleas, Nora; Fine, Paul V A

2017-11-01

Using complementary metrics to evaluate phylogenetic diversity can facilitate the delimitation of floristic units and conservation priority areas. In this study, we describe the spatial patterns of phylogenetic alpha and beta diversity, phylogenetic endemism, and evolutionary distinctiveness of the hyperdiverse Ecuador Amazon forests and define priority areas for conservation. We established a network of 62 one-hectare plots in terra firme forests of Ecuadorian Amazon. In these plots, we tagged, collected, and identified every single adult tree with dbh ≥10 cm. These data were combined with a regional community phylogenetic tree to calculate different phylogenetic diversity (PD) metrics in order to create spatial models. We used Loess regression to estimate the spatial variation of taxonomic and phylogenetic beta diversity as well as phylogenetic endemism and evolutionary distinctiveness. We found evidence for the definition of three floristic districts in the Ecuadorian Amazon, supported by both taxonomic and phylogenetic diversity data. Areas with high levels of phylogenetic endemism and evolutionary distinctiveness in Ecuadorian Amazon forests are unprotected. Furthermore, these areas are severely threatened by proposed plans of oil and mining extraction at large scales and should be prioritized in conservation planning for this region.

Monogenean anchor morphometry: systematic value, phylogenetic signal, and evolution

Science.gov (United States)

Soo, Oi Yoon Michelle; Tan, Wooi Boon; Lim, Lee Hong Susan

2016-01-01

Background. Anchors are one of the important attachment appendages for monogenean parasites. Common descent and evolutionary processes have left their mark on anchor morphometry, in the form of patterns of shape and size variation useful for systematic and evolutionary studies. When combined with morphological and molecular data, analysis of anchor morphometry can potentially answer a wide range of biological questions. Materials and Methods. We used data from anchor morphometry, body size and morphology of 13 Ligophorus (Monogenea: Ancyrocephalidae) species infecting two marine mugilid (Teleostei: Mugilidae) fish hosts: Moolgarda buchanani (Bleeker) and Liza subviridis (Valenciennes) from Malaysia. Anchor shape and size data (n = 530) were generated using methods of geometric morphometrics. We used 28S rRNA, 18S rRNA, and ITS1 sequence data to infer a maximum likelihood phylogeny. We discriminated species using principal component and cluster analysis of shape data. Adams’s Kmult was used to detect phylogenetic signal in anchor shape. Phylogeny-correlated size and shape changes were investigated using continuous character mapping and directional statistics, respectively. We assessed morphological constraints in anchor morphometry using phylogenetic regression of anchor shape against body size and anchor size. Anchor morphological integration was studied using partial least squares method. The association between copulatory organ morphology and anchor shape and size in phylomorphospace was used to test the Rohde-Hobbs hypothesis. We created monogeneaGM, a new R package that integrates analyses of monogenean anchor geometric morphometric data with morphological and phylogenetic data. Results. We discriminated 12 of the 13 Ligophorus species using anchor shape data. Significant phylogenetic signal was detected in anchor shape. Thus, we discovered new morphological characters based on anchor shaft shape, the length between the inner root point and the outer root

A phylogenetic comparison of urease-positive thermophilic Campylobacter (UPTC) and urease-negative (UN) C. lari.

Science.gov (United States)

Hirayama, Junichi; Tazumi, Akihiro; Hayashi, Kyohei; Tasaki, Erina; Kuribayashi, Takashi; Moore, John E; Millar, Beverley C; Matsuda, Motoo

2011-06-01

In the present study, the reliability of full-length gene sequence information for several genes including 16S rRNA was examined, for the discrimination of the two representative Campylobacter lari taxa, namely urease-negative (UN) C. lari and urease-positive thermophilic Campylobacter (UPTC). As previously described, 16S rRNA gene sequence are not reliable for the molecular discrimination of UN C. lari from UPTC organisms employing both the unweighted pair group method using arithmetic means analysis (UPGMA) and neighbor joining (NJ) methods. In addition, three composite full-length gene sequences (ciaB, flaC and vacJ) out of seven gene loci examined were reliable for discrimination employing dendrograms constructed by the UPGMA method. In addition, all the dendrograms of the NJ phylogenetic trees constructed based on the nine gene information were not reliable for the discrimination. Three composite full-length gene sequences (ciaB, flaC and vacJ) were reliable for the molecular discrimination between UN C. lari and UPTC organisms employing the UPGMA method, as well as among four thermophilic Campylobacter species. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid and reliable discrimination between Shigella species and Escherichia coli using MALDI-TOF mass spectrometry

NARCIS (Netherlands)

Paauw, A.; Jonker, D.; Roeselers, G.; Heng, J.M.E.; Mars-Groenendijk, R.H.; Trip, H.; Molhoek, E.M.; Jansen, H.J.; Plas, J. van der; Jong, A.L. de; Majchrzykiewicz-Koehorst, J.A.; Speksnijder, A.G.C.L.

2015-01-01

E. coli-. Shigella species are a cryptic group of bacteria in which the Shigella species are distributed within the phylogenetic tree of E. coli. The nomenclature is historically based and the discrimination of these genera developed as a result of the epidemiological need to identify the cause of

Relation between functional connectivity and rhythm discrimination in children who do and do not stutter

Directory of Open Access Journals (Sweden)

Soo-Eun Chang

2016-01-01

Full Text Available Our ability to perceive and produce rhythmic patterns in the environment supports fundamental human capacities ranging from music and language processing to the coordination of action. This article considers whether spontaneous correlated brain activity within a basal ganglia-thalamocortical (rhythm network is associated with individual differences in auditory rhythm discrimination. Moreover, do children who stutter with demonstrated deficits in rhythm perception have weaker links between rhythm network functional connectivity and rhythm discrimination? All children in the study underwent a resting-state fMRI session, from which functional connectivity measures within the rhythm network were extracted from spontaneous brain activity. In a separate session, the same children completed an auditory rhythm-discrimination task, where behavioral performance was assessed using signal detection analysis. We hypothesized that in typically developing children, rhythm network functional connectivity would be associated with behavioral performance on the rhythm discrimination task, but that this relationship would be attenuated in children who stutter. Results supported our hypotheses, lending strong support for the view that (1 children who stutter have weaker rhythm network connectivity and (2 the lack of a relation between rhythm network connectivity and rhythm discrimination in children who stutter may be an important contributing factor to the etiology of stuttering.

Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales

OpenAIRE

Purschke, Oliver; Michalski, Stefan G.; Bruelheide, Helge; Durka, Walter

2017-01-01

Abstract Although spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scales, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic ...

Discrimination among adults with craniofacial conditions.

Science.gov (United States)

Roberts, Rachel M

2014-01-01

The primary goal of this study was to establish the level of perceived discrimination experienced by adults with congenital craniofacial conditions in Australia and to examine predictors of discrimination. Specifically, this study tested whether social support mediates the relationship between discrimination and health. Adults (n = 93) who had been treated at the Australian Craniofacial Unit, Women's and Children's Hospital, Adelaide for congenital craniofacial conditions (not including cleft lip and/or palate) completed questionnaires examining satisfaction with life, quality of life, anxiety and depression, self-esteem, satisfaction with social support, and satisfaction with appearance. A substantial minority of adults with congenital craniofacial conditions reported that they experience discrimination almost every day in a range of areas. Higher reports of discrimination were related to older age, being male, and less education. Other factors related to higher discrimination included lower levels of satisfaction with life, self-esteem, satisfaction with appearance and mental quality of life, as well as higher levels of anxiety and depression. Social support partially mediated the relationship between discrimination and mental health outcomes. The current study shows that discrimination experiences continue into adulthood confirming the importance of ensuring patients are well supported both by psychosocial services as well as within their own social support networks.

The Development of Three Long Universal Nuclear Protein-Coding Locus Markers and Their Application to Osteichthyan Phylogenetics with Nested PCR

Science.gov (United States)

Zhang, Peng

2012-01-01

Background Universal nuclear protein-coding locus (NPCL) markers that are applicable across diverse taxa and show good phylogenetic discrimination have broad applications in molecular phylogenetic studies. For example, RAG1, a representative NPCL marker, has been successfully used to make phylogenetic inferences within all major osteichthyan groups. However, such markers with broad working range and high phylogenetic performance are still scarce. It is necessary to develop more universal NPCL markers comparable to RAG1 for osteichthyan phylogenetics. Methodology/Principal Findings We developed three long universal NPCL markers (>1.6 kb each) based on single-copy nuclear genes (KIAA1239, SACS and TTN) that possess large exons and exhibit the appropriate evolutionary rates. We then compared their phylogenetic utilities with that of the reference marker RAG1 in 47 jawed vertebrate species. In comparison with RAG1, each of the three long universal markers yielded similar topologies and branch supports, all in congruence with the currently accepted osteichthyan phylogeny. To compare their phylogenetic performance visually, we also estimated the phylogenetic informativeness (PI) profile for each of the four long universal NPCL markers. The PI curves indicated that SACS performed best over the whole timescale, while RAG1, KIAA1239 and TTN exhibited similar phylogenetic performances. In addition, we compared the success of nested PCR and standard PCR when amplifying NPCL marker fragments. The amplification success rate and efficiency of the nested PCR were overwhelmingly higher than those of standard PCR. Conclusions/Significance Our work clearly demonstrates the superiority of nested PCR over the conventional PCR in phylogenetic studies and develops three long universal NPCL markers (KIAA1239, SACS and TTN) with the nested PCR strategy. The three markers exhibit high phylogenetic utilities in osteichthyan phylogenetics and can be widely used as pilot genes for

Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

Science.gov (United States)

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

On Determining if Tree-based Networks Contain Fixed Trees.

Science.gov (United States)

Anaya, Maria; Anipchenko-Ulaj, Olga; Ashfaq, Aisha; Chiu, Joyce; Kaiser, Mahedi; Ohsawa, Max Shoji; Owen, Megan; Pavlechko, Ella; St John, Katherine; Suleria, Shivam; Thompson, Keith; Yap, Corrine

2016-05-01

We address an open question of Francis and Steel about phylogenetic networks and trees. They give a polynomial time algorithm to decide if a phylogenetic network, N, is tree-based and pose the problem: given a fixed tree T and network N, is N based on T? We show that it is [Formula: see text]-hard to decide, by reduction from 3-Dimensional Matching (3DM) and further that the problem is fixed-parameter tractable.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae in a phylogenetic context.

Directory of Open Access Journals (Sweden)

Maria Elvira Poleti Martucci

Full Text Available Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus. Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Phylogenetic Distribution of Leaf Spectra and Optically Derived Functional Traits in the American Oaks

Science.gov (United States)

Cavender-Bares, J.; Meireles, J. E.; Couture, J. J.; Kaproth, M.; Townsend, P. A.

2015-12-01

Detecting functional traits of species, genotypes and phylogenetic lineages is critical in monitoring functional biodiversity remotely. We examined the phylogenetic distribution of leaf spectra across the American Oaks for 35 species under greenhouse conditions as well as genetic variation in leaf spectra across Central American populations of a single species grown in common gardens in Honduras. We found significant phylogenetic signal in the leaf spectra (Blomberg's K > 1.0), indicating similarity in spectra among close relatives. Across species, full range leaf spectra were used in a Partial Least Squares Discriminant Analysis (PLS-DA) that allowed species calibration (kappa statistic = 0.55). Validation of the model used to detect species (kappa statistic = 0.4) indicated reasonably good detection of individual species within the same the genus. Among four populations from Belize, Costa Rica, Honduras, and Mexico within a single species (Quercus oleoides), leaf spectra were also able to differentiate populations. Ordination of population-level data using dissimilarities of predicted foliar traits, including leaf mass per area (LMA), lignin content, fiber content, chlorophyll a+b, and C:N ratio in genotypes in either watered or unwatered conditions showed significant differentiation among populations and treatments. These results provide promise for remote detection and differentiation of plant functional traits among plant phylogenetic lineages and genotypes, even among closely related populations and species.

A neurocomputational model of figure-ground discrimination and target tracking.

Science.gov (United States)

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

A discrimination technique for extensive air showers based on multiscale, lacunarity and neural network analysis

International Nuclear Information System (INIS)

Pagliaro, Antonio; D'Ali Staiti, G.; D'Anna, F.

2011-01-01

We present a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. In the present work the method is discussed and applied to a set of fully simulated vertical showers, in the experimental framework of ARGO-YBJ, to obtain hadron to gamma primary separation. We show that the presented approach gives very good results, leading, in the 1-10 TeV energy range, to a clear improvement of the discrimination power with respect to the existing figures for extended shower detectors.

Untangling hybrid phylogenetic signals: horizontal gene transfer and artifacts of phylogenetic reconstruction.

Science.gov (United States)

Beiko, Robert G; Ragan, Mark A

2009-01-01

Phylogenomic methods can be used to investigate the tangled evolutionary relationships among genomes. Building 'all the trees of all the genes' can potentially identify common pathways of horizontal gene transfer (HGT) among taxa at varying levels of phylogenetic depth. Phylogenetic affinities can be aggregated and merged with the information about genetic linkage and biochemical function to examine hypotheses of adaptive evolution via HGT. Additionally, the use of many genetic data sets increases the power of statistical tests for phylogenetic artifacts. However, large-scale phylogenetic analyses pose several challenges, including the necessary abandonment of manual validation techniques, the need to translate inferred phylogenetic discordance into inferred HGT events, and the challenges involved in aggregating results from search-based inference methods. In this chapter we describe a tree search procedure to recover the most parsimonious pathways of HGT, and examine some of the assumptions that are made by this method.

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

DEFF Research Database (Denmark)

Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

2012-01-01

Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...... phylogenetic profiles often require very different RT sets to support high prediction accuracy....

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

Directory of Open Access Journals (Sweden)

Christopher E Hart

2006-12-01

Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

Detecting taxonomic and phylogenetic signals in equid cheek teeth: towards new palaeontological and archaeological proxies

Science.gov (United States)

Mohaseb, A.; Peigné, S.; Debue, K.; Orlando, L.; Mashkour, M.

2017-01-01

The Plio–Pleistocene evolution of Equus and the subsequent domestication of horses and donkeys remains poorly understood, due to the lack of phenotypic markers capable of tracing this evolutionary process in the palaeontological/archaeological record. Using images from 345 specimens, encompassing 15 extant taxa of equids, we quantified the occlusal enamel folding pattern in four mandibular cheek teeth with a single geometric morphometric protocol. We initially investigated the protocol accuracy by assigning each tooth to its correct anatomical position and taxonomic group. We then contrasted the phylogenetic signal present in each tooth shape with an exome-wide phylogeny from 10 extant equine species. We estimated the strength of the phylogenetic signal using a Brownian motion model of evolution with multivariate K statistic, and mapped the dental shape along the molecular phylogeny using an approach based on squared-change parsimony. We found clear evidence for the relevance of dental phenotypes to accurately discriminate all modern members of the genus Equus and capture their phylogenetic relationships. These results are valuable for both palaeontologists and zooarchaeologists exploring the spatial and temporal dynamics of the evolutionary history of the horse family, up to the latest domestication trajectories of horses and donkeys. PMID:28484618

Functional discrimination of membrane proteins using machine learning techniques

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Yabuki Yukimitsu

2008-03-01

Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

Generative adversarial networks for brain lesion detection

Science.gov (United States)

Alex, Varghese; Safwan, K. P. Mohammed; Chennamsetty, Sai Saketh; Krishnamurthi, Ganapathy

2017-02-01

Manual segmentation of brain lesions from Magnetic Resonance Images (MRI) is cumbersome and introduces errors due to inter-rater variability. This paper introduces a semi-supervised technique for detection of brain lesion from MRI using Generative Adversarial Networks (GANs). GANs comprises of a Generator network and a Discriminator network which are trained simultaneously with the objective of one bettering the other. The networks were trained using non lesion patches (n=13,000) from 4 different MR sequences. The network was trained on BraTS dataset and patches were extracted from regions excluding tumor region. The Generator network generates data by modeling the underlying probability distribution of the training data, (PData). The Discriminator learns the posterior probability P (Label Data) by classifying training data and generated data as "Real" or "Fake" respectively. The Generator upon learning the joint distribution, produces images/patches such that the performance of the Discriminator on them are random, i.e. P (Label Data = GeneratedData) = 0.5. During testing, the Discriminator assigns posterior probability values close to 0.5 for patches from non lesion regions, while patches centered on lesion arise from a different distribution (PLesion) and hence are assigned lower posterior probability value by the Discriminator. On the test set (n=14), the proposed technique achieves whole tumor dice score of 0.69, sensitivity of 91% and specificity of 59%. Additionally the generator network was capable of generating non lesion patches from various MR sequences.

A Maximum Parsimony Model to Reconstruct Phylogenetic Network in Honey Bee Evolution

OpenAIRE

Usha Chouhan; K. R. Pardasani

2007-01-01

Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hyb...

Phylogenetic Analysis Using Protein Mass Spectrometry.

Science.gov (United States)

Ma, Shiyong; Downard, Kevin M; Wong, Jason W H

2017-01-01

Through advances in molecular biology, comparative analysis of DNA sequences is currently the cornerstone in the study of molecular evolution and phylogenetics. Nevertheless, protein mass spectrometry offers some unique opportunities to enable phylogenetic analyses in organisms where DNA may be difficult or costly to obtain. To date, the methods of phylogenetic analysis using protein mass spectrometry can be classified into three categories: (1) de novo protein sequencing followed by classical phylogenetic reconstruction, (2) direct phylogenetic reconstruction using proteolytic peptide mass maps, and (3) mapping of mass spectral data onto classical phylogenetic trees. In this chapter, we provide a brief description of the three methods and the protocol for each method along with relevant tools and algorithms.

Development of the optical sensor for discriminating isomers of fatty acids based on emissive network polymers composed of polyhedral oligomeric silsesquioxane.

Science.gov (United States)

Narikiyo, Hayato; Kakuta, Takahiro; Matsuyama, Hiroki; Gon, Masayuki; Tanaka, Kazuo; Chujo, Yoshiki

2017-07-01

It was shown that water-soluble network polymers composed of polyhedral oligomeric silsesquioxane (POSS) had hydrophobic spaces inside the network because of strong hydrophobicity of the cubic silica cage. In this study, the water-soluble POSS network polymers connected with triphenylamine derivatives (TPA-POSS) were synthesized, and their functions as a sensor for discriminating the geometric isomers of fatty acids were investigated. Accordingly, in the photoluminescence spectra, different time-courses of intensity and peak wavelengths of the emission bands were detected from the TPA-POSS-containing solution in the presence of cis- or trans-fatty acids during incubation. Furthermore, variable time-dependent changes were obtained by changing coexisting ratios between two geometric isomers. From the mechanistic investigation, it was implied that these changes could be originated from the difference in the degree of interaction between the POSS networks and each fatty acid. Our data could be applicable for constructing a sensing material for generation and proportion of trans-fatty acids in the oil. Copyright © 2017 Elsevier Ltd. All rights reserved.

High similarity of phylogenetic profiles of rate-limiting enzymes with inhibitory relation in Human, Mouse, Rat, budding Yeast and E. coli.

Science.gov (United States)

Zhao, Min; Qu, Hong

2011-11-30

The phylogenetic profile is widely used to characterize functional linkage and conservation between proteins without amino acid sequence similarity. To survey the conservative regulatory properties of rate-limiting enzymes (RLEs) in metabolic inhibitory network across different species, we define the enzyme inhibiting pair as: where the first enzyme in a pair is the inhibitor provider and the second is the target of the inhibitor. Phylogenetic profiles of enzymes in the inhibiting pairs are further generated to measure the functional linkage of these enzymes during evolutionary history. We find that the RLEs generate, on average, over half of all in vivo inhibitors in each surveyed model organism. And these inhibitors inhibit on average over 85% targets in metabolic inhibitory network and cover the majority of targets of cross-pathway inhibiting relations. Furthermore, we demonstrate that the phylogenetic profiles of the enzymes in inhibiting pairs in which at least one enzyme is rate-limiting often show higher similarities than those in common inhibiting enzyme pairs. In addition, RLEs, compared to common metabolic enzymes, often tend to produce ADP instead of AMP in conservative inhibitory networks. Combined with the conservative roles of RLEs in their efficiency in sensing metabolic signals and transmitting regulatory signals to the rest of the metabolic system, the RLEs may be important molecules in balancing energy homeostasis via maintaining the ratio of ATP to ADP in living cells. Furthermore, our results indicate that similarities of phylogenetic profiles of enzymes in the inhibiting enzyme pairs are not only correlated with enzyme topological importance, but also related with roles of the enzymes in metabolic inhibitory network.

Functional and phylogenetic ecology in R

CERN Document Server

Swenson, Nathan G

2014-01-01

Functional and Phylogenetic Ecology in R is designed to teach readers to use R for phylogenetic and functional trait analyses. Over the past decade, a dizzying array of tools and methods were generated to incorporate phylogenetic and functional information into traditional ecological analyses. Increasingly these tools are implemented in R, thus greatly expanding their impact. Researchers getting started in R can use this volume as a step-by-step entryway into phylogenetic and functional analyses for ecology in R. More advanced users will be able to use this volume as a quick reference to understand particular analyses. The volume begins with an introduction to the R environment and handling relevant data in R. Chapters then cover phylogenetic and functional metrics of biodiversity; null modeling and randomizations for phylogenetic and functional trait analyses; integrating phylogenetic and functional trait information; and interfacing the R environment with a popular C-based program. This book presents a uni...

A format for phylogenetic placements.

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Frederick A Matsen

Full Text Available We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.

Phylogenetic inertia and Darwin's higher law.

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Shanahan, Timothy

2011-03-01

The concept of 'phylogenetic inertia' is routinely deployed in evolutionary biology as an alternative to natural selection for explaining the persistence of characteristics that appear sub-optimal from an adaptationist perspective. However, in many of these contexts the precise meaning of 'phylogenetic inertia' and its relationship to selection are far from clear. After tracing the history of the concept of 'inertia' in evolutionary biology, I argue that treating phylogenetic inertia and natural selection as alternative explanations is mistaken because phylogenetic inertia is, from a Darwinian point of view, simply an expected effect of selection. Although Darwin did not discuss 'phylogenetic inertia,' he did assert the explanatory priority of selection over descent. An analysis of 'phylogenetic inertia' provides a perspective from which to assess Darwin's view. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modeling documents with Generative Adversarial Networks

OpenAIRE

Glover, John

2016-01-01

This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

Structural Discrimination and Autonomous Vehicles

DEFF Research Database (Denmark)

Liu, Hin-Yan

2016-01-01

This paper examines the potential for structural discrimination to be woven into the fabric of autonomous vehicle developments, which remain underexplored and undiscussed. The prospect for structural discrimination arises as a result of the coordinated modes of autonomous vehicle behaviour...... individual identity, and potentially relative worth, to autonomous vehicles engaging in a crash damage calculus. At the risk of introducing these ideas into the development of autonomous vehicles, this paper hopes to spark a debate to foreclose these eventualities....... that is prescribed by its code. This leads to the potential for individuated outcomes to be networked and thereby multiplied consistently to any number of vehicles implementing such a code. The aggregated effects of such algorithmic policy preferences will thus cumulate in the reallocation of benefits and burdens...

The transposition distance for phylogenetic trees

OpenAIRE

Rossello, Francesc; Valiente, Gabriel

2006-01-01

The search for similarity and dissimilarity measures on phylogenetic trees has been motivated by the computation of consensus trees, the search by similarity in phylogenetic databases, and the assessment of clustering results in bioinformatics. The transposition distance for fully resolved phylogenetic trees is a recent addition to the extensive collection of available metrics for comparing phylogenetic trees. In this paper, we generalize the transposition distance from fully resolved to arbi...

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Science.gov (United States)

2010-01-01

Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Directory of Open Access Journals (Sweden)

Dawyndt Peter

2010-01-01

Full Text Available Abstract Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the

From learning taxonomies to phylogenetic learning: integration of 16S rRNA gene data into FAME-based bacterial classification.

Science.gov (United States)

Slabbinck, Bram; Waegeman, Willem; Dawyndt, Peter; De Vos, Paul; De Baets, Bernard

2010-01-30

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial

Integrative taxonomy of ciliates: Assessment of molecular phylogenetic content and morphological homology testing.

Science.gov (United States)

Vďačný, Peter

2017-10-01

The very diverse and comparatively complex morphology of ciliates has given rise to numerous taxonomic concepts. However, the information content of the utilized molecular markers has seldom been explored prior to phylogenetic analyses and taxonomic decisions. Likewise, robust testing of morphological homology statements and the apomorphic nature of diagnostic characters of ciliate taxa is rarely carried out. Four phylogenetic techniques that may help address these issues are reviewed. (1) Split spectrum analysis serves to determine the exact number and quality of nucleotide positions supporting individual nodes in phylogenetic trees and to discern long-branch artifacts that cause spurious phylogenies. (2) Network analysis can depict all possible evolutionary trajectories inferable from the dataset and locate and measure the conflict between them. (3) A priori likelihood mapping tests the suitability of data for reconstruction of a well resolved tree, visualizes the tree-likeness of quartets, and assesses the support of an internal branch of a given tree topology. (4) Reconstruction of ancestral morphologies can be applied for analyzing homology and apomorphy statements without circular reasoning. Since these phylogenetic tools are rarely used, their principles and interpretation are introduced and exemplified using various groups of ciliates. Finally, environmental sequencing data are discussed in this light. Copyright © 2017 The Author. Published by Elsevier GmbH.. All rights reserved.

Phylogenetic Trees From Sequences

Science.gov (United States)

Ryvkin, Paul; Wang, Li-San

In this chapter, we review important concepts and approaches for phylogeny reconstruction from sequence data.We first cover some basic definitions and properties of phylogenetics, and briefly explain how scientists model sequence evolution and measure sequence divergence. We then discuss three major approaches for phylogenetic reconstruction: distance-based phylogenetic reconstruction, maximum parsimony, and maximum likelihood. In the third part of the chapter, we review how multiple phylogenies are compared by consensus methods and how to assess confidence using bootstrapping. At the end of the chapter are two sections that list popular software packages and additional reading.

The phylogenetic likelihood library.

Science.gov (United States)

Flouri, T; Izquierdo-Carrasco, F; Darriba, D; Aberer, A J; Nguyen, L-T; Minh, B Q; Von Haeseler, A; Stamatakis, A

2015-03-01

We introduce the Phylogenetic Likelihood Library (PLL), a highly optimized application programming interface for developing likelihood-based phylogenetic inference and postanalysis software. The PLL implements appropriate data structures and functions that allow users to quickly implement common, error-prone, and labor-intensive tasks, such as likelihood calculations, model parameter as well as branch length optimization, and tree space exploration. The highly optimized and parallelized implementation of the phylogenetic likelihood function and a thorough documentation provide a framework for rapid development of scalable parallel phylogenetic software. By example of two likelihood-based phylogenetic codes we show that the PLL improves the sequential performance of current software by a factor of 2-10 while requiring only 1 month of programming time for integration. We show that, when numerical scaling for preventing floating point underflow is enabled, the double precision likelihood calculations in the PLL are up to 1.9 times faster than those in BEAGLE. On an empirical DNA dataset with 2000 taxa the AVX version of PLL is 4 times faster than BEAGLE (scaling enabled and required). The PLL is available at http://www.libpll.org under the GNU General Public License (GPL). © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

A precision timing discriminator for high density detector systems

International Nuclear Information System (INIS)

Turko, B.T.; Smith, R.C.

1992-01-01

Most high resolution time measurement techniques require discriminators that accurately make the time arrival of events regardless of their intensity. Constant fraction discriminators or zero-crossing discriminators are generally used. In this paper, the authors describe a zero-crossing discriminator that accurately determines the peak of a quasi-Gaussian waveform by differentiating it and detecting the resulting zero-crossing. Basically, it consists of a fast voltage comparator and tow integrating networks: an RC section and an LR section used in a way that keeps the input impedance purely resistive. A time walk of 100 ps in an amplitude range exceeding 100:1 has been achieved for wave-forms from 1.5 ns to 15 ns FWHM. An arming level discriminator is added to eliminate triggering by noise. Easily implemented in either monolithic or hybrid technology, the circuit is suitable for large multichannel detector systems where size and power dissipation are crucial. Circuit diagrams and typical measured data are also presented

Molecular Phylogenetics: Concepts for a Newcomer.

Science.gov (United States)

Ajawatanawong, Pravech

Molecular phylogenetics is the study of evolutionary relationships among organisms using molecular sequence data. The aim of this review is to introduce the important terminology and general concepts of tree reconstruction to biologists who lack a strong background in the field of molecular evolution. Some modern phylogenetic programs are easy to use because of their user-friendly interfaces, but understanding the phylogenetic algorithms and substitution models, which are based on advanced statistics, is still important for the analysis and interpretation without a guide. Briefly, there are five general steps in carrying out a phylogenetic analysis: (1) sequence data preparation, (2) sequence alignment, (3) choosing a phylogenetic reconstruction method, (4) identification of the best tree, and (5) evaluating the tree. Concepts in this review enable biologists to grasp the basic ideas behind phylogenetic analysis and also help provide a sound basis for discussions with expert phylogeneticists.

A shared system of representation governing quantity discrimination in canids

Directory of Open Access Journals (Sweden)

Joseph M Baker

2012-10-01

Full Text Available One way to investigate the evolution of cognition is to compare the abilities of phylogenetically related species. The domestic dog (Canis lupus familiaris, for example, still shares cognitive abilities with the coyote (C. latrans. Both of these canids possess the ability to make psychophysical less/more discriminations of food based on quantity. Like many other species including humans, this ability is mediated by Weber’s Law: discrimination of continuous quantities is dependent on the ratio between the two quantities. As two simultaneously presented quantities of food become more similar, choice of the large or small option becomes random in both dogs and coyotes. It remains unknown, however, whether these closely related species within the same family—one domesticated, and one wild—make such quantitative comparisons with comparable accuracy. Has domestication honed or diminished this quantitative ability? Might different selective and ecological pressures facing coyotes drive them to be more or less able to accurately represent and discriminate food quantity than domesticated dogs? This study is an effort to elucidate this question concerning the evolution of non-verbal quantitative cognition.Here, we tested the quantitative discrimination ability of 16 domesticated dogs. Each animal was given 9 trials in which two different quantities of food were simultaneously displayed to them. The domesticated dogs’ performance on this task was then compared directly to the data from 16 coyotes’ performance on this same task reported by Baker and colleagues (2011.The quantitative discrimination abilities between the two species were strikingly similar. Domesticated dogs demonstrated similar quantitative sensitivity as coyotes, suggesting that domestication may not have significantly altered the psychophysical discrimination abilities of canids. Instead, this study provides further evidence for similar nonverbal quantitative abilities across

Universal artifacts affect the branching of phylogenetic trees, not universal scaling laws.

Science.gov (United States)

Altaba, Cristian R

2009-01-01

for tree shape convergence of large trees. There is no evidence for any universal scaling in the tree of life. Instead, there is a need for improved methods of tree analysis that can be used to discriminate the noise due to outgroups from the phylogenetic signal within the taxon of interest, and to evaluate realistic models of evolution, correcting the retrospective perspective and explicitly recognizing extinction as a driving force. Artifacts are pervasive, and can only be overcome through understanding the structure and biological meaning of phylogenetic trees. Catalan Abstract in Translation S1.

How discriminating are discriminative instruments?

Science.gov (United States)

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

How discriminating are discriminative instruments?

Directory of Open Access Journals (Sweden)

Hankins Matthew

2008-05-01

Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

Encoding phylogenetic trees in terms of weighted quartets.

Science.gov (United States)

Grünewald, Stefan; Huber, Katharina T; Moulton, Vincent; Semple, Charles

2008-04-01

One of the main problems in phylogenetics is to develop systematic methods for constructing evolutionary or phylogenetic trees. For a set of species X, an edge-weighted phylogenetic X-tree or phylogenetic tree is a (graph theoretical) tree with leaf set X and no degree 2 vertices, together with a map assigning a non-negative length to each edge of the tree. Within phylogenetics, several methods have been proposed for constructing such trees that work by trying to piece together quartet trees on X, i.e. phylogenetic trees each having four leaves in X. Hence, it is of interest to characterise when a collection of quartet trees corresponds to a (unique) phylogenetic tree. Recently, Dress and Erdös provided such a characterisation for binary phylogenetic trees, that is, phylogenetic trees all of whose internal vertices have degree 3. Here we provide a new characterisation for arbitrary phylogenetic trees.

Tree phylogenetic diversity promotes host-parasitoid interactions.

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Staab, Michael; Bruelheide, Helge; Durka, Walter; Michalski, Stefan; Purschke, Oliver; Zhu, Chao-Dong; Klein, Alexandra-Maria

2016-07-13

Evidence from grassland experiments suggests that a plant community's phylogenetic diversity (PD) is a strong predictor of ecosystem processes, even stronger than species richness per se This has, however, never been extended to species-rich forests and host-parasitoid interactions. We used cavity-nesting Hymenoptera and their parasitoids collected in a subtropical forest as a model system to test whether hosts, parasitoids, and their interactions are influenced by tree PD and a comprehensive set of environmental variables, including tree species richness. Parasitism rate and parasitoid abundance were positively correlated with tree PD. All variables describing parasitoids decreased with elevation, and were, except parasitism rate, dependent on host abundance. Quantitative descriptors of host-parasitoid networks were independent of the environment. Our study indicates that host-parasitoid interactions in species-rich forests are related to the PD of the tree community, which influences parasitism rates through parasitoid abundance. We show that effects of tree community PD are much stronger than effects of tree species richness, can cascade to high trophic levels, and promote trophic interactions. As during habitat modification phylogenetic information is usually lost non-randomly, even species-rich habitats may not be able to continuously provide the ecosystem process parasitism if the evolutionarily most distinct plant lineages vanish. © 2016 The Author(s).

HIV-1 transmission networks in high risk fishing communities on the shores of Lake Victoria in Uganda: A phylogenetic and epidemiological approach.

Directory of Open Access Journals (Sweden)

Sylvia Kiwuwa-Muyingo

Full Text Available Fishing communities around Lake Victoria in sub-Saharan Africa have been characterised as a population at high risk of HIV-infection.Using data from a cohort of HIV-positive individuals aged 13-49 years, enrolled from 5 fishing communities on Lake Victoria between 2009-2011, we sought to identify factors contributing to the epidemic and to understand the underlying structure of HIV transmission networks. Clinical and socio-demographic data were combined with HIV-1 phylogenetic analyses. HIV-1 gag-p24 and env-gp-41 sub-genomic fragments were amplified and sequenced from 283 HIV-1-infected participants. Phylogenetic clusters with ≥2 highly related sequences were defined as transmission clusters. Logistic regression models were used to determine factors associated with clustering.Altogether, 24% (n = 67/283 of HIV positive individuals with sequences fell within 34 phylogenetically distinct clusters in at least one gene region (either gag or env. Of these, 83% occurred either within households or within community; 8/34 (24% occurred within household partnerships, and 20/34 (59% within community. 7/12 couples (58% within households clustered together. Individuals in clusters with potential recent transmission (11/34 were more likely to be younger 71% (15/21 versus 46% (21/46 in un-clustered individuals and had recently become resident in the community 67% (14/21 vs 48% (22/46. Four of 11 (36% potential transmission clusters included incident-incident transmissions. Independently, clustering was less likely in HIV subtype D (adjusted Odds Ratio, aOR = 0.51 [95% CI 0.26-1.00] than A and more likely in those living with an HIV-infected individual in the household (aOR = 6.30 [95% CI 3.40-11.68].A large proportion of HIV sexual transmissions occur within house-holds and within communities even in this key mobile population. The findings suggest localized HIV transmissions and hence a potential benefit for the test and treat approach even at a community

Shifts in color discrimination during early pregnancy.

Science.gov (United States)

Orbán, Levente L; Dastur, Farhad N

2012-05-25

The present study explores two hypotheses: a) women during early pregnancy should experience increased color discrimination ability, and b) women during early pregnancy should experience shifts in subjective preference away from images of foods that appear either unripe or spoiled. Both of these hypotheses derive from an adaptive view of pregnancy sickness that proposes the function of pregnancy sickness is to decrease the likelihood of ingestion of foods with toxins or teratogens. Changes to color discrimination could be part of a network of perceptual and physiological defenses (e.g., changes to olfaction, nausea, vomiting) that support such a function. Participants included 13 pregnant women and 18 non-pregnant women. Pregnant women scored significantly higher than non-pregnant controls on the Farnsworth-Munsell (FM) 100 Hue Test, an objective test of color discrimination, although no difference was found between groups in preferences for food images at different stages of ripeness or spoilage. These results are the first indication that changes to color discrimination may occur during early pregnancy, and is consistent with the view that pregnancy sickness may function as an adaptive defense mechanism.

Ecological, historical and evolutionary determinants of modularity in weighted seed-dispersal networks

DEFF Research Database (Denmark)

Schleuning, Matthias; Ingmann, Lili; Strauß, Rouven

2014-01-01

Modularity is a recurrent and important property of bipartite ecological networks. Although well-resolved ecological networks describe interaction frequencies between species pairs, modularity of bipartite networks has been analysed only on the basis of binary presence-absence data. We employ a new...... algorithm to detect modularity in weighted bipartite networks in a global analysis of avian seed-dispersal networks. We define roles of species, such as connector values, for weighted and binary networks and associate them with avian species traits and phylogeny. The weighted, but not binary, analysis...... identified a positive relationship between climatic seasonality and modularity, whereas past climate stability and phylogenetic signal were only weakly related to modularity. Connector values were associated with foraging behaviour and were phylogenetically conserved. The weighted modularity analysis...

Mapping Discrimination Experienced by Indonesian Trans* FtM Persons.

Science.gov (United States)

Gordon, Danny; Pratama, Mario Prajna

2017-01-01

This work sought to document how Indonesian trans* FtM persons experienced discrimination across the interlinked domains of social networks, religious and educational institutions, employment and the workplace, and health care institutions. Objectives were (1) to map the discrimination experienced by trans* FtM individuals in Indonesia, and (2) to establish the specific priorities of the Indonesian trans* FtM community. In-depth interviews, focus groups, and participant observation was used involving 14 respondents. Findings revealed that respondents experienced othering through rejection, misidentification, harassment, "correction," and bureaucratic discrimination across the five preestablished domains. Health care and a lack of information emerged as areas of particular concern for respondents. This work calls for health care that is sensitive to the needs of trans* FtM people coupled with high-quality information to alleviate the cycles through which discrimination is sustained.

Global patterns of amphibian phylogenetic diversity

DEFF Research Database (Denmark)

Fritz, Susanne; Rahbek, Carsten

2012-01-01

Aim  Phylogenetic diversity can provide insight into how evolutionary processes may have shaped contemporary patterns of species richness. Here, we aim to test for the influence of phylogenetic history on global patterns of amphibian species richness, and to identify areas where macroevolutionary...... processes such as diversification and dispersal have left strong signatures on contemporary species richness. Location  Global; equal-area grid cells of approximately 10,000 km2. Methods  We generated an amphibian global supertree (6111 species) and repeated analyses with the largest available molecular...... phylogeny (2792 species). We combined each tree with global species distributions to map four indices of phylogenetic diversity. To investigate congruence between global spatial patterns of amphibian species richness and phylogenetic diversity, we selected Faith’s phylogenetic diversity (PD) index...

Suitability of Root and Rhizome Anatomy for Taxonomic Classification and Reconstruction of Phylogenetic Relationships in the Tribes Cardueae and Cichorieae (Asteraceae).

Science.gov (United States)

Ginko, Elisabeth; Dobeš, Christoph; Saukel, Johannes

2016-05-27

The value of root and rhizome anatomy for the taxonomic characterisation of 59 species classified into 34 genera and 12 subtribes from the Asteraceae tribes Cardueae and Cichorieae was assessed. In addition, the evolutionary history of anatomical characters was reconstructed using a nuclear ribosomal DNA sequence-based phylogeny of the Cichorieae. Taxa were selected with a focus on pharmaceutically relevant species. A binary decision tree was constructed and discriminant function analyses were performed to extract taxonomically relevant anatomical characters and to infer the separability of infratribal taxa, respectively. The binary decision tree distinguished 33 species and two subspecies, but only five of the genera (sampled for at least two species) by a unique combination of hierarchically arranged characters. Accessions were discriminated-except for one sample worthy of discussion-according to their subtribal affiliation in the discriminant function analyses (DFA). However, constantly expressed subtribe-specific characters were almost missing and even in combination, did not discriminate the subtribes. Most anatomical characters showed at least some degree of homoplasious evolution limiting their suitability as phylogenetically informative characters.

Nodal distances for rooted phylogenetic trees.

Science.gov (United States)

Cardona, Gabriel; Llabrés, Mercè; Rosselló, Francesc; Valiente, Gabriel

2010-08-01

Dissimilarity measures for (possibly weighted) phylogenetic trees based on the comparison of their vectors of path lengths between pairs of taxa, have been present in the systematics literature since the early seventies. For rooted phylogenetic trees, however, these vectors can only separate non-weighted binary trees, and therefore these dissimilarity measures are metrics only on this class of rooted phylogenetic trees. In this paper we overcome this problem, by splitting in a suitable way each path length between two taxa into two lengths. We prove that the resulting splitted path lengths matrices single out arbitrary rooted phylogenetic trees with nested taxa and arcs weighted in the set of positive real numbers. This allows the definition of metrics on this general class of rooted phylogenetic trees by comparing these matrices through metrics in spaces M(n)(R) of real-valued n x n matrices. We conclude this paper by establishing some basic facts about the metrics for non-weighted phylogenetic trees defined in this way using L(p) metrics on M(n)(R), with p [epsilon] R(>0).

Ant-Based Phylogenetic Reconstruction (ABPR: A new distance algorithm for phylogenetic estimation based on ant colony optimization

Directory of Open Access Journals (Sweden)

Karla Vittori

2008-12-01

Full Text Available We propose a new distance algorithm for phylogenetic estimation based on Ant Colony Optimization (ACO, named Ant-Based Phylogenetic Reconstruction (ABPR. ABPR joins two taxa iteratively based on evolutionary distance among sequences, while also accounting for the quality of the phylogenetic tree built according to the total length of the tree. Similar to optimization algorithms for phylogenetic estimation, the algorithm allows exploration of a larger set of nearly optimal solutions. We applied the algorithm to four empirical data sets of mitochondrial DNA ranging from 12 to 186 sequences, and from 898 to 16,608 base pairs, and covering taxonomic levels from populations to orders. We show that ABPR performs better than the commonly used Neighbor-Joining algorithm, except when sequences are too closely related (e.g., population-level sequences. The phylogenetic relationships recovered at and above species level by ABPR agree with conventional views. However, like other algorithms of phylogenetic estimation, the proposed algorithm failed to recover expected relationships when distances are too similar or when rates of evolution are very variable, leading to the problem of long-branch attraction. ABPR, as well as other ACO-based algorithms, is emerging as a fast and accurate alternative method of phylogenetic estimation for large data sets.

Physical activity discrimination improvement using accelerometers and wireless sensor network localization - biomed 2013.

Science.gov (United States)

Bashford, Gregory R; Burnfield, Judith M; Perez, Lance C

2013-01-01

Automating documentation of physical activity data (e.g., duration and speed of walking or propelling a wheelchair) into the electronic medical record (EMR) offers promise for improving efficiency of documentation and understanding of best practices in the rehabilitation and home health settings. Commercially available devices which could be used to automate documentation of physical activities are either cumbersome to wear or lack the specificity required to differentiate activities. We have designed a novel system to differentiate and quantify physical activities, using inexpensive accelerometer-based biomechanical data technology and wireless sensor networks, a technology combination that has not been used in a rehabilitation setting to date. As a first step, a feasibility study was performed where 14 healthy young adults (mean age = 22.6 ± 2.5 years, mean height = 173 ± 10.0 cm, mean mass = 70.7 ± 11.3 kg) carried out eight different activities while wearing a biaxial accelerometer sensor. Activities were performed at each participant’s self-selected pace during a single testing session in a controlled environment. Linear discriminant analysis was performed by extracting spectral parameters from the subjects’ accelerometer patterns. It is shown that physical activity classification alone results in an average accuracy of 49.5%, but when combined with rule-based constraints using a wireless sensor network with localization capabilities in an in silico simulated room, accuracy improves to 99.3%. When fully implemented, our technology package is expected to improve goal setting, treatment interventions and patient outcomes by enhancing clinicians’ understanding of patients’ physical performance within a day and across the rehabilitation program.

Digital liquid-scintillation counting and effective pulse-shape discrimination with artificial neural networks

International Nuclear Information System (INIS)

Langrock, Gert; Wiehl, Norbert; Kling, Hans-Otto; Mendel, Matthias; Naehler, Andrea; Tharun, Udo; Eberhardt, Klaus; Trautmann, Norbert; Kratz, Jens Volker

2015-01-01

A typical problem in low-level liquid scintillation (LS) counting is the identification of α particles in the presence of a high background of β and γ particles. Especially the occurrence of β-β and β-γ pile-ups may prevent the unambiguous identification of an α signal by commonly used analog electronics. In this case, pulse-shape discrimination (PSD) and pile-up rejection (PUR) units show an insufficient performance. This problem was also observed in own earlier experiments on the chemical behaviour of transactinide elements using the liquid-liquid extraction system SISAK in combination with LS counting. α-particle signals from the decay of the transactinides could not be unambiguously assigned. However, the availability of instruments for the digital recording of LS pulses changes the situation and provides possibilities for new approaches in the treatment of LS pulse shapes. In a SISAK experiment performed at PSI, Villigen, a fast transient recorder, a PC card with oscilloscope characteristics and a sampling rate of 1 giga samples s -1 (1 ns per point), was used for the first time to record LS signals. It turned out, that the recorded signals were predominantly α β-β and β-γ pile up, and fission events. This paper describes the subsequent development and use of artificial neural networks (ANN) based on the method of 'back-propagation of errors' to automatically distinguish between different pulse shapes. Such networks can 'learn' pulse shapes and classify hitherto unknown pulses correctly after a learning period. The results show that ANN in combination with fast digital recording of pulse shapes can be a powerful tool in LS spectrometry even at high background count rates.

Network externalities in telecommunication industry: An analysis of Serbian market

Directory of Open Access Journals (Sweden)

Trifunović Dejan

2016-01-01

Full Text Available This paper deals with network competition and provides empirical analysis of market concentration, network and call externalities, access pricing, price discrimination and switching costs in Serbian mobile phone telecommunications market. It is shown that network externalities governed the expansion of this market until 2008. Upon entry of VIP incumbents didn't engage in predatory behaviour towards entrant aiming to benefit from locked- in users. The policy of mobile phone number portability reduced on-net prices and substantially increased consumer's surplus. In contrast to some previous research, this policy was pro-competitive in Serbia. We have also determined that users of the network with the largest market share benefit the most from call externalities. Finally, one network does not price discriminate between outgoing and incoming roaming calls, which implies that users of this network have higher level pecuniary externalities in roaming compared to users of price discriminating networks.

Comparative evolutionary diversity and phylogenetic structure across multiple forest dynamics plots: a mega-phylogeny approach

Directory of Open Access Journals (Sweden)

David Lee Erickson

2014-11-01

Full Text Available Forest dynamics plots, which now span longitudes, latitudes, and habitat types across the globe, offer unparalleled insights into the ecological and evolutionary processes that determine how species are assembled into communities. Understanding phylogenetic relationships among species in a community has become an important component of assessing assembly processes. However, the application of evolutionary information to questions in community ecology has been limited in large part by the lack of accurate estimates of phylogenetic relationships among individual species found within communities, and is particularly limiting in comparisons between communities. Therefore, streamlining and maximizing the information content of these community phylogenies is a priority. To test the viability and advantage of a multi-community phylogeny, we constructed a multi-plot mega-phylogeny of 1,347 species of trees across 15 forest dynamics plots in the ForestGEO network using DNA barcode sequence data (rbcL, matK and psbA-trnH and compared community phylogenies for each individual plot with respect to support for topology and branch lengths, which affect evolutionary inference of community processes. The levels of taxonomic differentiation across the phylogeny were examined by quantifying the frequency of resolved nodes throughout. In addition, three phylogenetic distance metrics that are commonly used to infer assembly processes were estimated for each plot (Phylogenetic Distance [PD], Mean Phylogenetic Distance [MPD], and Mean Nearest Taxon Distance [MNTD]. Lastly, we examine the partitioning of phylogenetic diversity among community plots through quantification of inter-community MPD and MNTD. Overall, evolutionary relationships were highly resolved across the DNA barcode-based mega-phylogeny, and phylogenetic resolution for each community plot was improved when estimated within the context of the mega-phylogeny. Likewise, when compared with phylogenies for

Spatial discrimination and visual discrimination

DEFF Research Database (Denmark)

Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

2013-01-01

Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

Functional & phylogenetic diversity of copepod communities

Science.gov (United States)

Benedetti, F.; Ayata, S. D.; Blanco-Bercial, L.; Cornils, A.; Guilhaumon, F.

2016-02-01

The diversity of natural communities is classically estimated through species identification (taxonomic diversity) but can also be estimated from the ecological functions performed by the species (functional diversity), or from the phylogenetic relationships among them (phylogenetic diversity). Estimating functional diversity requires the definition of specific functional traits, i.e., phenotypic characteristics that impact fitness and are relevant to ecosystem functioning. Estimating phylogenetic diversity requires the description of phylogenetic relationships, for instance by using molecular tools. In the present study, we focused on the functional and phylogenetic diversity of copepod surface communities in the Mediterranean Sea. First, we implemented a specific trait database for the most commonly-sampled and abundant copepod species of the Mediterranean Sea. Our database includes 191 species, described by seven traits encompassing diverse ecological functions: minimal and maximal body length, trophic group, feeding type, spawning strategy, diel vertical migration and vertical habitat. Clustering analysis in the functional trait space revealed that Mediterranean copepods can be gathered into groups that have different ecological roles. Second, we reconstructed a phylogenetic tree using the available sequences of 18S rRNA. Our tree included 154 of the analyzed Mediterranean copepod species. We used these two datasets to describe the functional and phylogenetic diversity of copepod surface communities in the Mediterranean Sea. The replacement component (turn-over) and the species richness difference component (nestedness) of the beta diversity indices were identified. Finally, by comparing various and complementary aspects of plankton diversity (taxonomic, functional, and phylogenetic diversity) we were able to gain a better understanding of the relationships among the zooplankton community, biodiversity, ecosystem function, and environmental forcing.

treespace: Statistical exploration of landscapes of phylogenetic trees.

Science.gov (United States)

Jombart, Thibaut; Kendall, Michelle; Almagro-Garcia, Jacob; Colijn, Caroline

2017-11-01

The increasing availability of large genomic data sets as well as the advent of Bayesian phylogenetics facilitates the investigation of phylogenetic incongruence, which can result in the impossibility of representing phylogenetic relationships using a single tree. While sometimes considered as a nuisance, phylogenetic incongruence can also reflect meaningful biological processes as well as relevant statistical uncertainty, both of which can yield valuable insights in evolutionary studies. We introduce a new tool for investigating phylogenetic incongruence through the exploration of phylogenetic tree landscapes. Our approach, implemented in the R package treespace, combines tree metrics and multivariate analysis to provide low-dimensional representations of the topological variability in a set of trees, which can be used for identifying clusters of similar trees and group-specific consensus phylogenies. treespace also provides a user-friendly web interface for interactive data analysis and is integrated alongside existing standards for phylogenetics. It fills a gap in the current phylogenetics toolbox in R and will facilitate the investigation of phylogenetic results. © 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

Phylogenetic diversity and relationships among species of genus ...

African Journals Online (AJOL)

Fifty six Nicotiana species were used to construct phylogenetic trees and to asses the genetic relationships between them. Genetic distances estimated from RAPD analysis was used to construct phylogenetic trees using Phylogenetic Inference Package (PHYLIP). Since phylogenetic relationships estimated for closely ...

Moderation of the effects of discrimination-induced affective responses on health outcomes.

Science.gov (United States)

Gerrard, Meg; Gibbons, Frederick X; Fleischli, Mary E; Cutrona, Carolyn E; Stock, Michelle L

2018-02-01

The goal of the study was to examine differential mediation of long-term effects of discrimination on health behaviour and health status by internalising (anxiety and depression) and externalising (hostility and anger), and to explore moderation of these effects, specifically, by the presence of support networks and coping tendencies. The current analyses employed structural equation modelling of five waves of data from Black female participants of the Family and Community Health Study over 11 years (M age 37-48). The main outcome variables were health status and alcohol use (frequency and problematic consumption). Perceived racial discrimination was associated with increases in internalising and externalising. In addition, internalising reactions to discrimination were associated with deterioration in health status and increases in problematic drinking; externalising reactions were associated with increases in frequency of drinking. These relations were attenuated by availability of support networks, and exacerbated by use of avoidance coping. The current study (a) replicated previous research suggesting that two different types of affective reactions mediate the relations between perceived racial discrimination and physical health status vs. health-impairing behaviours: internalising and externalising, and (b) revealed moderation of these effects by coping mechanisms.

Shifts in Color Discrimination during Early Pregnancy

Directory of Open Access Journals (Sweden)

Levente L. Orbán

2012-04-01

Full Text Available The present study explores two hypotheses: a women during early pregnancy should experience increased color discrimination ability, and b women during early pregnancy should experience shifts in subjective preference away from images of foods that appear either unripe or spoiled. Both of these hypotheses derive from an adaptive view of pregnancy sickness that proposes the function of pregnancy sickness is to decrease the likelihood of ingestion of foods with toxins or teratogens. Changes to color discrimination could be part of a network of perceptual and physiological defenses (e.g., changes to olfaction, nausea, vomiting that support such a function. Participants included 13 pregnant women and 18 non-pregnant women. Pregnant women scored significantly higher than non-pregnant controls on the Farnsworth-Munsell (FM 100 Hue Test, an objective test of color discrimination, although no difference was found between groups in preferences for food images at different stages of ripeness or spoilage. These results are the first indication that changes to color discrimination may occur during early pregnancy, and is consistent with the view that pregnancy sickness may function as an adaptive defense mechanism.

constNJ: an algorithm to reconstruct sets of phylogenetic trees satisfying pairwise topological constraints.

Science.gov (United States)

Matsen, Frederick A

2010-06-01

This article introduces constNJ (constrained neighbor-joining), an algorithm for phylogenetic reconstruction of sets of trees with constrained pairwise rooted subtree-prune-regraft (rSPR) distance. We are motivated by the problem of constructing sets of trees that must fit into a recombination, hybridization, or similar network. Rather than first finding a set of trees that are optimal according to a phylogenetic criterion (e.g., likelihood or parsimony) and then attempting to fit them into a network, constNJ estimates the trees while enforcing specified rSPR distance constraints. The primary input for constNJ is a collection of distance matrices derived from sequence blocks which are assumed to have evolved in a tree-like manner, such as blocks of an alignment which do not contain any recombination breakpoints. The other input is a set of rSPR constraint inequalities for any set of pairs of trees. constNJ is consistent and a strict generalization of the neighbor-joining algorithm; it uses the new notion of maximum agreement partitions (MAPs) to assure that the resulting trees satisfy the given rSPR distance constraints.

Ultrafast Approximation for Phylogenetic Bootstrap

NARCIS (Netherlands)

Bui Quang Minh, [No Value; Nguyen, Thi; von Haeseler, Arndt

Nonparametric bootstrap has been a widely used tool in phylogenetic analysis to assess the clade support of phylogenetic trees. However, with the rapidly growing amount of data, this task remains a computational bottleneck. Recently, approximation methods such as the RAxML rapid bootstrap (RBS) and

Discrimination and Anti-discrimination in Denmark

DEFF Research Database (Denmark)

Olsen, Tore Vincents

The purpose of this report is to describe and analyse Danish anti-discrimination legislation and the debate about discrimination in Denmark in order to identify present and future legal challenges. The main focus is the implementation of the EU anti-discrimination directives in Danish law...

Different relationships between temporal phylogenetic turnover and phylogenetic similarity and in two forests were detected by a new null model.

Science.gov (United States)

Huang, Jian-Xiong; Zhang, Jian; Shen, Yong; Lian, Ju-yu; Cao, Hong-lin; Ye, Wan-hui; Wu, Lin-fang; Bin, Yue

2014-01-01

Ecologists have been monitoring community dynamics with the purpose of understanding the rates and causes of community change. However, there is a lack of monitoring of community dynamics from the perspective of phylogeny. We attempted to understand temporal phylogenetic turnover in a 50 ha tropical forest (Barro Colorado Island, BCI) and a 20 ha subtropical forest (Dinghushan in southern China, DHS). To obtain temporal phylogenetic turnover under random conditions, two null models were used. The first shuffled names of species that are widely used in community phylogenetic analyses. The second simulated demographic processes with careful consideration on the variation in dispersal ability among species and the variations in mortality both among species and among size classes. With the two models, we tested the relationships between temporal phylogenetic turnover and phylogenetic similarity at different spatial scales in the two forests. Results were more consistent with previous findings using the second null model suggesting that the second null model is more appropriate for our purposes. With the second null model, a significantly positive relationship was detected between phylogenetic turnover and phylogenetic similarity in BCI at a 10 m×10 m scale, potentially indicating phylogenetic density dependence. This relationship in DHS was significantly negative at three of five spatial scales. This could indicate abiotic filtering processes for community assembly. Using variation partitioning, we found phylogenetic similarity contributed to variation in temporal phylogenetic turnover in the DHS plot but not in BCI plot. The mechanisms for community assembly in BCI and DHS vary from phylogenetic perspective. Only the second null model detected this difference indicating the importance of choosing a proper null model.

Undergraduate Students’ Difficulties in Reading and Constructing Phylogenetic Tree

Science.gov (United States)

Sa'adah, S.; Tapilouw, F. S.; Hidayat, T.

2017-02-01

Representation is a very important communication tool to communicate scientific concepts. Biologists produce phylogenetic representation to express their understanding of evolutionary relationships. The phylogenetic tree is visual representation depict a hypothesis about the evolutionary relationship and widely used in the biological sciences. Phylogenetic tree currently growing for many disciplines in biology. Consequently, learning about phylogenetic tree become an important part of biological education and an interesting area for biology education research. However, research showed many students often struggle with interpreting the information that phylogenetic trees depict. The purpose of this study was to investigate undergraduate students’ difficulties in reading and constructing a phylogenetic tree. The method of this study is a descriptive method. In this study, we used questionnaires, interviews, multiple choice and open-ended questions, reflective journals and observations. The findings showed students experiencing difficulties, especially in constructing a phylogenetic tree. The students’ responds indicated that main reasons for difficulties in constructing a phylogenetic tree are difficult to placing taxa in a phylogenetic tree based on the data provided so that the phylogenetic tree constructed does not describe the actual evolutionary relationship (incorrect relatedness). Students also have difficulties in determining the sister group, character synapomorphy, autapomorphy from data provided (character table) and comparing among phylogenetic tree. According to them building the phylogenetic tree is more difficult than reading the phylogenetic tree. Finding this studies provide information to undergraduate instructor and students to overcome learning difficulties of reading and constructing phylogenetic tree.

The atmospheric signal of terrestrial carbon isotopic discrimination and its implication for partitioning carbon fluxes

International Nuclear Information System (INIS)

Miller, John B.; Tans, Pieter P.; Conway, Thomas J.; White, James W.C.; Vaughn, Bruce W.

2003-01-01

The 13 C/ 12 C ratio in atmospheric carbon dioxide has been measured in samples taken in the NOAA/CMDL network since 1991. By examining the relationship between weekly anomalies in 13 C and CO 2 at continental sites in the network, we infer temporal and spatial values for the isotopic signature of terrestrial CO 2 fluxes. We can convert these isotopic signatures to values of discrimination if we assume the atmospheric starting point for photosynthesis. The average discrimination in the Northern Hemisphere between 30 and 50 deg N is calculated to be 16.6 ± 0.2 per mil. In contrast to some earlier modeling studies, we find no strong latitudinal gradient in discrimination. However, we do observe that discrimination in Eurasia is larger than in North America, which is consistent with two modeling studies. We also observe a possible trend in the North American average of discrimination toward less discrimination. There is no apparent trend in the Eurasian average or at any individual sites. However, there is interannual variability on the order of 2 per mil at several sites and regions. Finally, we calculate the northern temperate terrestrial CO 2 flux replacing our previous discrimination values of about 18 per mil with the average value of 16.6 calculated in this study. We find this enhances the terrestrial sink by about 0.4 GtC/yr

Phylogenetic structure in tropical hummingbird communities

DEFF Research Database (Denmark)

Graham, Catherine H; Parra, Juan L; Rahbek, Carsten

2009-01-01

How biotic interactions, current and historical environment, and biogeographic barriers determine community structure is a fundamental question in ecology and evolution, especially in diverse tropical regions. To evaluate patterns of local and regional diversity, we quantified the phylogenetic...... composition of 189 hummingbird communities in Ecuador. We assessed how species and phylogenetic composition changed along environmental gradients and across biogeographic barriers. We show that humid, low-elevation communities are phylogenetically overdispersed (coexistence of distant relatives), a pattern...... that is consistent with the idea that competition influences the local composition of hummingbirds. At higher elevations communities are phylogenetically clustered (coexistence of close relatives), consistent with the expectation of environmental filtering, which may result from the challenge of sustaining...

Constructing phylogenetic trees using interacting pathways.

Science.gov (United States)

Wan, Peng; Che, Dongsheng

2013-01-01

Phylogenetic trees are used to represent evolutionary relationships among biological species or organisms. The construction of phylogenetic trees is based on the similarities or differences of their physical or genetic features. Traditional approaches of constructing phylogenetic trees mainly focus on physical features. The recent advancement of high-throughput technologies has led to accumulation of huge amounts of biological data, which in turn changed the way of biological studies in various aspects. In this paper, we report our approach of building phylogenetic trees using the information of interacting pathways. We have applied hierarchical clustering on two domains of organisms-eukaryotes and prokaryotes. Our preliminary results have shown the effectiveness of using the interacting pathways in revealing evolutionary relationships.

Phylogenetic classification of yeasts and related taxa within Pucciniomycotina.

Science.gov (United States)

Wang, Q-M; Yurkov, A M; Göker, M; Lumbsch, H T; Leavitt, S D; Groenewald, M; Theelen, B; Liu, X-Z; Boekhout, T; Bai, F-Y

2015-06-01

Most small genera containing yeast species in the Pucciniomycotina (Basidiomycota, Fungi) are monophyletic, whereas larger genera including Bensingtonia, Rhodosporidium, Rhodotorula, Sporidiobolus and Sporobolomyces are polyphyletic. With the implementation of the "One Fungus = One Name" nomenclatural principle these polyphyletic genera were revised. Nine genera, namely Bannoa, Cystobasidiopsis, Colacogloea, Kondoa, Erythrobasidium, Rhodotorula, Sporobolomyces, Sakaguchia and Sterigmatomyces, were emended to include anamorphic and teleomorphic species based on the results obtained by a multi-gene phylogenetic analysis, phylogenetic network analyses, branch length-based methods, as well as morphological, physiological and biochemical comparisons. A new class Spiculogloeomycetes is proposed to accommodate the order Spiculogloeales. The new families Buckleyzymaceae with Buckleyzyma gen. nov., Chrysozymaceae with Chrysozyma gen. nov., Microsporomycetaceae with Microsporomyces gen. nov., Ruineniaceae with Ruinenia gen. nov., Symmetrosporaceae with Symmetrospora gen. nov., Colacogloeaceae and Sakaguchiaceae are proposed. The new genera Bannozyma, Buckleyzyma, Fellozyma, Hamamotoa, Hasegawazyma, Jianyunia, Rhodosporidiobolus, Oberwinklerozyma, Phenoliferia, Pseudobensingtonia, Pseudohyphozyma, Sampaiozyma, Slooffia, Spencerozyma, Trigonosporomyces, Udeniozyma, Vonarxula, Yamadamyces and Yunzhangia are proposed to accommodate species segregated from the genera Bensingtonia, Rhodosporidium, Rhodotorula, Sporidiobolus and Sporobolomyces. Ballistosporomyces is emended and reintroduced to include three Sporobolomyces species of the sasicola clade. A total of 111 new combinations are proposed in this study.

Digital liquid-scintillation counting and effective pulse-shape discrimination with artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Langrock, Gert; Wiehl, Norbert; Kling, Hans-Otto; Mendel, Matthias; Naehler, Andrea; Tharun, Udo; Eberhardt, Klaus; Trautmann, Norbert; Kratz, Jens Volker [Mainz Univ. (Germany). Inst. fuer Kernchemie; Omtvedt, Jon-Petter [Oslo Univ. (Norway). Dept. of Chemistry; Skarnemark, Gunnar [Chalmers Univ. of Technology, Goeteborg (Sweden)

2015-05-01

A typical problem in low-level liquid scintillation (LS) counting is the identification of α particles in the presence of a high background of β and γ particles. Especially the occurrence of β-β and β-γ pile-ups may prevent the unambiguous identification of an α signal by commonly used analog electronics. In this case, pulse-shape discrimination (PSD) and pile-up rejection (PUR) units show an insufficient performance. This problem was also observed in own earlier experiments on the chemical behaviour of transactinide elements using the liquid-liquid extraction system SISAK in combination with LS counting. α-particle signals from the decay of the transactinides could not be unambiguously assigned. However, the availability of instruments for the digital recording of LS pulses changes the situation and provides possibilities for new approaches in the treatment of LS pulse shapes. In a SISAK experiment performed at PSI, Villigen, a fast transient recorder, a PC card with oscilloscope characteristics and a sampling rate of 1 giga samples s{sup -1} (1 ns per point), was used for the first time to record LS signals. It turned out, that the recorded signals were predominantly α β-β and β-γ pile up, and fission events. This paper describes the subsequent development and use of artificial neural networks (ANN) based on the method of 'back-propagation of errors' to automatically distinguish between different pulse shapes. Such networks can 'learn' pulse shapes and classify hitherto unknown pulses correctly after a learning period. The results show that ANN in combination with fast digital recording of pulse shapes can be a powerful tool in LS spectrometry even at high background count rates.

Hippocampal-cortical contributions to strategic exploration during perceptual discrimination.

Science.gov (United States)

Voss, Joel L; Cohen, Neal J

2017-06-01

The hippocampus is crucial for long-term memory; its involvement in short-term or immediate expressions of memory is more controversial. Rodent hippocampus has been implicated in an expression of memory that occurs on-line during exploration termed "vicarious trial-and-error" (VTE) behavior. VTE occurs when rodents iteratively explore options during perceptual discrimination or at choice points. It is strategic in that it accelerates learning and improves later memory. VTE has been associated with activity of rodent hippocampal neurons, and lesions of hippocampus disrupt VTE and associated learning and memory advantages. Analogous findings of VTE in humans would support the role of hippocampus in active use of short-term memory to guide strategic behavior. We therefore measured VTE using eye-movement tracking during perceptual discrimination and identified relevant neural correlates with functional magnetic resonance imaging. A difficult perceptual-discrimination task was used that required visual information to be maintained during a several second trial, but with no long-term memory component. VTE accelerated discrimination. Neural correlates of VTE included robust activity of hippocampus and activity of a network of medial prefrontal and lateral parietal regions involved in memory-guided behavior. This VTE-related activity was distinct from activity associated with simply viewing visual stimuli and making eye movements during the discrimination task, which occurred in regions frequently associated with visual processing and eye-movement control. Subjects were mostly unaware of performing VTE, thus further distancing VTE from explicit long-term memory processing. These findings bridge the rodent and human literatures on neural substrates of memory-guided behavior, and provide further support for the role of hippocampus and a hippocampal-centered network of cortical regions in the immediate use of memory in on-line processing and the guidance of behavior. © 2017

Phylogenetic classification of bony fishes.

Science.gov (United States)

Betancur-R, Ricardo; Wiley, Edward O; Arratia, Gloria; Acero, Arturo; Bailly, Nicolas; Miya, Masaki; Lecointre, Guillaume; Ortí, Guillermo

2017-07-06

Fish classifications, as those of most other taxonomic groups, are being transformed drastically as new molecular phylogenies provide support for natural groups that were unanticipated by previous studies. A brief review of the main criteria used by ichthyologists to define their classifications during the last 50 years, however, reveals slow progress towards using an explicit phylogenetic framework. Instead, the trend has been to rely, in varying degrees, on deep-rooted anatomical concepts and authority, often mixing taxa with explicit phylogenetic support with arbitrary groupings. Two leading sources in ichthyology frequently used for fish classifications (JS Nelson's volumes of Fishes of the World and W. Eschmeyer's Catalog of Fishes) fail to adopt a global phylogenetic framework despite much recent progress made towards the resolution of the fish Tree of Life. The first explicit phylogenetic classification of bony fishes was published in 2013, based on a comprehensive molecular phylogeny ( www.deepfin.org ). We here update the first version of that classification by incorporating the most recent phylogenetic results. The updated classification presented here is based on phylogenies inferred using molecular and genomic data for nearly 2000 fishes. A total of 72 orders (and 79 suborders) are recognized in this version, compared with 66 orders in version 1. The phylogeny resolves placement of 410 families, or ~80% of the total of 514 families of bony fishes currently recognized. The ordinal status of 30 percomorph families included in this study, however, remains uncertain (incertae sedis in the series Carangaria, Ovalentaria, or Eupercaria). Comments to support taxonomic decisions and comparisons with conflicting taxonomic groups proposed by others are presented. We also highlight cases were morphological support exist for the groups being classified. This version of the phylogenetic classification of bony fishes is substantially improved, providing resolution

The space of ultrametric phylogenetic trees.

Science.gov (United States)

Gavryushkin, Alex; Drummond, Alexei J

2016-08-21

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data. Hence the question of statistical consistency of such methods is equivalent to the consistency of the summary of the sample. More generally, statistical consistency is ensured by the tree space used to analyse the sample. In this paper, we consider two standard parameterisations of phylogenetic time-trees used in evolutionary models: inter-coalescent interval lengths and absolute times of divergence events. For each of these parameterisations we introduce a natural metric space on ultrametric phylogenetic trees. We compare the introduced spaces with existing models of tree space and formulate several formal requirements that a metric space on phylogenetic trees must possess in order to be a satisfactory space for statistical analysis, and justify them. We show that only a few known constructions of the space of phylogenetic trees satisfy these requirements. However, our results suggest that these basic requirements are not enough to distinguish between the two metric spaces we introduce and that the choice between metric spaces requires additional properties to be considered. Particularly, that the summary tree minimising the square distance to the trees from the sample might be different for different parameterisations. This suggests that further fundamental insight is needed into the problem of statistical consistency of phylogenetic inference methods. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

phangorn: phylogenetic analysis in R.

Science.gov (United States)

Schliep, Klaus Peter

2011-02-15

phangorn is a package for phylogenetic reconstruction and analysis in the R language. Previously it was only possible to estimate phylogenetic trees with distance methods in R. phangorn, now offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation. Extending the general ML framework, this package provides the possibility of estimating mixture and partition models. Furthermore, phangorn offers several functions for comparing trees, phylogenetic models or splits, simulating character data and performing congruence analyses. phangorn can be obtained through the CRAN homepage http://cran.r-project.org/web/packages/phangorn/index.html. phangorn is licensed under GPL 2.

Rapid discrimination and classification of the Lactobacillus plantarum group based on a partial dnaK sequence and DNA fingerprinting techniques.

Science.gov (United States)

Huang, Chien-Hsun; Lee, Fwu-Ling; Liou, Jong-Shian

2010-03-01

The Lactobacillus plantarum group comprises five very closely related species. Some species of this group are considered to be probiotic and widely applied in the food industry. In this study, we compared the use of two different molecular markers, the 16S rRNA and dnaK gene, for discriminating phylogenetic relationships amongst L. plantarum strains using sequencing and DNA fingerprinting. The average sequence similarity for the dnaK gene (89.2%) among five type strains was significantly less than that for the 16S rRNA (99.4%). This result demonstrates that the dnaK gene sequence provided higher resolution than the 16S rRNA and suggests that the dnaK could be used as an additional phylogenetic marker for L. plantarum. Species-specific profiles of the Lactobacillus strains were obtained with RAPD and RFLP methods. Our data indicate that phylogenetic relationships between these strains are easily resolved using sequencing of the dnaK gene or DNA fingerprinting assays.

A CMOS integrated timing discriminator circuit for fast scintillation counters

International Nuclear Information System (INIS)

Jochmann, M.W.

1998-01-01

Based on a zero-crossing discriminator using a CR differentiation network for pulse shaping, a new CMOS integrated timing discriminator circuit is proposed for fast (t r ≥ 2 ns) scintillation counters at the cooler synchrotron COSY-Juelich. By eliminating the input signal's amplitude information by means of an analog continuous-time divider, a normalized pulse shape at the zero-crossing point is gained over a wide dynamic input amplitude range. In combination with an arming comparator and a monostable multivibrator this yields in a highly precise timing discriminator circuit, that is expected to be useful in different time measurement applications. First measurement results of a CMOS integrated logarithmic amplifier, which is part of the analog continuous-time divider, agree well with the corresponding simulations. Moreover, SPICE simulations of the integrated discriminator circuit promise a time walk well below 200 ps (FWHM) over a 40 dB input amplitude dynamic range

Undergraduate Students’ Initial Ability in Understanding Phylogenetic Tree

Science.gov (United States)

Sa'adah, S.; Hidayat, T.; Sudargo, Fransisca

2017-04-01

The Phylogenetic tree is a visual representation depicts a hypothesis about the evolutionary relationship among taxa. Evolutionary experts use this representation to evaluate the evidence for evolution. The phylogenetic tree is currently growing for many disciplines in biology. Consequently, learning about the phylogenetic tree has become an important part of biological education and an interesting area of biology education research. Skill to understanding and reasoning of the phylogenetic tree, (called tree thinking) is an important skill for biology students. However, research showed many students have difficulty in interpreting, constructing, and comparing among the phylogenetic tree, as well as experiencing a misconception in the understanding of the phylogenetic tree. Students are often not taught how to reason about evolutionary relationship depicted in the diagram. Students are also not provided with information about the underlying theory and process of phylogenetic. This study aims to investigate the initial ability of undergraduate students in understanding and reasoning of the phylogenetic tree. The research method is the descriptive method. Students are given multiple choice questions and an essay that representative by tree thinking elements. Each correct answer made percentages. Each student is also given questionnaires. The results showed that the undergraduate students’ initial ability in understanding and reasoning phylogenetic tree is low. Many students are not able to answer questions about the phylogenetic tree. Only 19 % undergraduate student who answered correctly on indicator evaluate the evolutionary relationship among taxa, 25% undergraduate student who answered correctly on indicator applying concepts of the clade, 17% undergraduate student who answered correctly on indicator determines the character evolution, and only a few undergraduate student who can construct the phylogenetic tree.

Recombination Blurs Phylogenetic Groups Routine Assignment in Escherichia coli: Setting the Record Straight

Science.gov (United States)

Turrientes, María-Carmen; González-Alba, José-María; del Campo, Rosa; Baquero, María-Rosario; Cantón, Rafael; Baquero, Fernando; Galán, Juan Carlos

2014-01-01

The characterization of population structures plays a main role for understanding outbreaks and the dynamics of bacterial spreading. In Escherichia coli, the widely used combination of multiplex-PCR scheme together with goeBURST has some limitations. The purpose of this study is to show that the combination of different phylogenetic approaches based on concatenated sequences of MLST genes results in a more precise assignment of E. coli phylogenetic groups, complete understanding of population structure and reconstruction of ancestral clones. A collection of 80 Escherichia coli strains of different origins was analyzed following the Clermont and Doumith's multiplex-PCR schemes. Doumith's multiplex-PCR showed only 1.7% of misassignment, whereas Clermont's-2000 protocol reached 14.0%, although the discrepancies reached 30% and 38.7% respectively when recombinant C, F and E phylogroups were considered. Therefore, correct phylogroup attribution is highly variable and depends on the clonal composition of the sample. As far as population structure of these E. coli strains, including 48 E. coli genomes from GenBank, goeBURST provides a quite dispersed population structure; whereas NeighborNet approach reveals a complex population structure. MLST-based eBURST can infer different founder genotypes, for instance ST23/ST88 could be detected as the founder genotypes for STC23; however, phylogenetic reconstructions might suggest ST410 as the ancestor clone and several evolutionary trajectories with different founders. To improve our routine understanding of E. coli molecular epidemiology, we propose a strategy based on three successive steps; first, to discriminate three main groups A/B1/C, D/F/E and B2 following Doumith's protocol; second, visualization of population structure based on MLST genes according to goeBURST, using NeighborNet to establish more complex relationships among STs; and third, to perform, a cost-free characterization of evolutionary trajectories in variants

Molecular phylogenetic trees - On the validity of the Goodman-Moore augmentation algorithm

Science.gov (United States)

Holmquist, R.

1979-01-01

A response is made to the reply of Nei and Tateno (1979) to the letter of Holmquist (1978) supporting the validity of the augmentation algorithm of Moore (1977) in reconstructions of nucleotide substitutions by means of the maximum parsimony principle. It is argued that the overestimation of the augmented numbers of nucleotide substitutions (augmented distances) found by Tateno and Nei (1978) is due to an unrepresentative data sample and that it is only necessary that evolution be stochastically uniform in different regions of the phylogenetic network for the augmentation method to be useful. The importance of the average value of the true distance over all links is explained, and the relative variances of the true and augmented distances are calculated to be almost identical. The effects of topological changes in the phylogenetic tree on the augmented distance and the question of the correctness of ancestral sequences inferred by the method of parsimony are also clarified.

Discrimination of Rice with Different Pretreatment Methods by Using a Voltammetric Electronic Tongue

Directory of Open Access Journals (Sweden)

Li Wang

2015-07-01

Full Text Available In this study, an application of a voltammetric electronic tongue for discrimination and prediction of different varieties of rice was investigated. Different pretreatment methods were selected, which were subsequently used for the discrimination of different varieties of rice and prediction of unknown rice samples. To this aim, a voltammetric array of sensors based on metallic electrodes was used as the sensing part. The different samples were analyzed by cyclic voltammetry with two sample-pretreatment methods. Discriminant Factorial Analysis was used to visualize the different categories of rice samples; however, radial basis function (RBF artificial neural network with leave-one-out cross-validation method was employed for prediction modeling. The collected signal data were first compressed employing fast Fourier transform (FFT and then significant features were extracted from the voltammetric signals. The experimental results indicated that the sample solutions obtained by the non-crushed pretreatment method could efficiently meet the effect of discrimination and recognition. The satisfactory prediction results of voltammetric electronic tongue based on RBF artificial neural network were obtained with less than five-fold dilution of the sample solution. The main objective of this study was to develop primary research on the application of an electronic tongue system for the discrimination and prediction of solid foods and provide an objective assessment tool for the food industry.

Phylogenetic tests of distribution patterns in South Asia: towards

Indian Academy of Sciences (India)

The last four decades have seen an increasing integration of phylogenetics and biogeography. However, a dearth of phylogenetic studies has precluded such biogeographic analyses in South Asia until recently. Noting the increase in phylogenetic research and interest in phylogenetic biogeography in the region, we ...

Fourier transform inequalities for phylogenetic trees.

Science.gov (United States)

Matsen, Frederick A

2009-01-01

Phylogenetic invariants are not the only constraints on site-pattern frequency vectors for phylogenetic trees. A mutation matrix, by its definition, is the exponential of a matrix with non-negative off-diagonal entries; this positivity requirement implies non-trivial constraints on the site-pattern frequency vectors. We call these additional constraints "edge-parameter inequalities". In this paper, we first motivate the edge-parameter inequalities by considering a pathological site-pattern frequency vector corresponding to a quartet tree with a negative internal edge. This site-pattern frequency vector nevertheless satisfies all of the constraints described up to now in the literature. We next describe two complete sets of edge-parameter inequalities for the group-based models; these constraints are square-free monomial inequalities in the Fourier transformed coordinates. These inequalities, along with the phylogenetic invariants, form a complete description of the set of site-pattern frequency vectors corresponding to bona fide trees. Said in mathematical language, this paper explicitly presents two finite lists of inequalities in Fourier coordinates of the form "monomial < or = 1", each list characterizing the phylogenetically relevant semialgebraic subsets of the phylogenetic varieties.

Using discriminant analysis to detect intrusions in external communication for self-driving vehicles

Directory of Open Access Journals (Sweden)

Khattab M.Ali Alheeti

2017-08-01

Full Text Available Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoc networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DoS and black hole attacks on vehicular ad hoc networks (VANETs. The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA and Quadratic Discriminant Analysis (QDA which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.

Phylogenetic search through partial tree mixing

Science.gov (United States)

2012-01-01

Background Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques. Results When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda Conclusions The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution. PMID:23320449

Phylogenetic Signal in AFLP Data Sets

NARCIS (Netherlands)

Koopman, W.J.M.

2005-01-01

AFLP markers provide a potential source of phylogenetic information for molecular systematic studies. However, there are properties of restriction fragment data that limit phylogenetic interpretation of AFLPs. These are (a) possible nonindependence of fragments, (b) problems of homology assignment

How does cognition evolve? Phylogenetic comparative psychology

Science.gov (United States)

Matthews, Luke J.; Hare, Brian A.; Nunn, Charles L.; Anderson, Rindy C.; Aureli, Filippo; Brannon, Elizabeth M.; Call, Josep; Drea, Christine M.; Emery, Nathan J.; Haun, Daniel B. M.; Herrmann, Esther; Jacobs, Lucia F.; Platt, Michael L.; Rosati, Alexandra G.; Sandel, Aaron A.; Schroepfer, Kara K.; Seed, Amanda M.; Tan, Jingzhi; van Schaik, Carel P.; Wobber, Victoria

2014-01-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution. PMID:21927850

How does cognition evolve? Phylogenetic comparative psychology.

Science.gov (United States)

MacLean, Evan L; Matthews, Luke J; Hare, Brian A; Nunn, Charles L; Anderson, Rindy C; Aureli, Filippo; Brannon, Elizabeth M; Call, Josep; Drea, Christine M; Emery, Nathan J; Haun, Daniel B M; Herrmann, Esther; Jacobs, Lucia F; Platt, Michael L; Rosati, Alexandra G; Sandel, Aaron A; Schroepfer, Kara K; Seed, Amanda M; Tan, Jingzhi; van Schaik, Carel P; Wobber, Victoria

2012-03-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution.

Phylogenetic reconstruction methods: an overview.

Science.gov (United States)

De Bruyn, Alexandre; Martin, Darren P; Lefeuvre, Pierre

2014-01-01

Initially designed to infer evolutionary relationships based on morphological and physiological characters, phylogenetic reconstruction methods have greatly benefited from recent developments in molecular biology and sequencing technologies with a number of powerful methods having been developed specifically to infer phylogenies from macromolecular data. This chapter, while presenting an overview of basic concepts and methods used in phylogenetic reconstruction, is primarily intended as a simplified step-by-step guide to the construction of phylogenetic trees from nucleotide sequences using fairly up-to-date maximum likelihood methods implemented in freely available computer programs. While the analysis of chloroplast sequences from various Vanilla species is used as an illustrative example, the techniques covered here are relevant to the comparative analysis of homologous sequences datasets sampled from any group of organisms.

Differential discriminator

International Nuclear Information System (INIS)

Dukhanov, V.I.; Mazurov, I.B.

1981-01-01

A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

Structural Discrimination

DEFF Research Database (Denmark)

Thorsen, Mira Skadegård

discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

Augmenting an observation network to facilitate flow and transport model discrimination.

Science.gov (United States)

Improving understanding of subsurface conditions includes performance comparison for competing models, independently developed or obtained via model abstraction. The model comparison and discrimination can be improved if additional observations will be included. The objective of this work was to i...

Lexical tonal discrimination in Zapotec children. A study of the theta rhythm.

Science.gov (United States)

Poblano, Adrián; Castro-Sierra, Eduardo; Arteaga, Carmina; Pérez-Ruiz, Santiago J

Zapotec is a language used mainly in the state of Oaxaca in Mexico of tonal characteristic; homophone words with difference in fundamental frequency with different meanings. Our objective was to analyze changes in the electroencephalographic (EEG) theta rhythm during word discrimination of lexical tonal bi-syllabic homophone word samples of Zapotec. We employed electroencephalography analysis during lexical tonal discrimination in 12 healthy subjects 9-16 years of age. We observed an increase in theta relative power between lexical discrimination and at rest eyes-open state in right temporal site. We also observed several significant intra- and inter-hemispheric correlations in several scalp sites, mainly in left fronto-temporal and right temporal areas when subjects were performing lexical discrimination. Our data suggest more engagement of neural networks of the right hemisphere are involved in Zapotec language discrimination. Copyright © 2015 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Limited Influence of Oxygen on the Evolution of Chemical Diversity in Metabolic Networks

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Kazuhiro Takemoto

2013-10-01

Full Text Available Oxygen is thought to promote species and biomolecule diversity. Previous studies have suggested that oxygen expands metabolic networks by acquiring metabolites with different chemical properties (higher hydrophobicity, for example. However, such conclusions are typically based on biased evaluation, and are therefore non-conclusive. Thus, we re-investigated the effect of oxygen on metabolic evolution using a phylogenetic comparative method and metadata analysis to reduce the bias as much as possible. Notably, we found no difference in metabolic network expansion between aerobes and anaerobes when evaluating phylogenetic relationships. Furthermore, we showed that previous studies have overestimated or underestimated the degrees of differences in the chemical properties (e.g., hydrophobicity between oxic and anoxic metabolites in metabolic networks of unicellular organisms; however, such overestimation was not observed when considering the metabolic networks of multicellular organisms. These findings indicate that the contribution of oxygen to increased chemical diversity in metabolic networks is lower than previously thought; rather, phylogenetic signals and cell-cell communication result in increased chemical diversity. However, this conclusion does not contradict the effect of oxygen on metabolic evolution; instead, it provides a deeper understanding of how oxygen contributes to metabolic evolution despite several limitations in data analysis methods.

Generating Seismograms with Deep Neural Networks

Science.gov (United States)

Krischer, L.; Fichtner, A.

2017-12-01

The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

Directory of Open Access Journals (Sweden)

Santana Isabel

2011-08-01

Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

Nucleotide diversity and phylogenetic relationships among ...

Indian Academy of Sciences (India)

NIRAJ SINGH

for phylogenetic analysis of Gladiolus and related taxa using combined datasets from chloroplast genome. The psbA–trnH ... phylogenetic relationships among cultivars could be useful for hybridization programmes for further improvement of the crop. [Singh N. ... breeding in nature, and exhibited diverse pollination mech-.

Examining Workplace Discrimination in a Discrimination-Free Environment

OpenAIRE

Braxton, Shawn Lamont

2010-01-01

Examining Workplace Discrimination in a Discrimination-Free Environment Shawn L. Braxton Abstract The purpose of this study is to explore how racial and gender discrimination is reproduced in concrete workplace settings even when anti-discrimination policies are present, and to understand the various reactions utilized by those who commonly experience it. I have selected a particular medical center, henceforth referred to by a pseudonym, â The Bliley Medical Centerâ as my case ...

Neural networks at the Tevatron

International Nuclear Information System (INIS)

Badgett, W.; Burkett, K.; Campbell, M.K.; Wu, D.Y.; Bianchin, S.; DeNardi, M.; Pauletta, G.; Santi, L.; Caner, A.; Denby, B.; Haggerty, H.; Lindsey, C.S.; Wainer, N.; Dall'Agata, M.; Johns, K.; Dickson, M.; Stanco, L.; Wyss, J.L.

1992-10-01

This paper summarizes neural network applications at the Fermilab Tevatron, including the first online hardware application in high energy physics (muon tracking): the CDF and DO neural network triggers; offline quark/gluon discrimination at CDF; ND a new tool for top to multijets recognition at CDF

Phylogenetic Position of Barbus lacerta Heckel, 1843

Directory of Open Access Journals (Sweden)

Mustafa Korkmaz

2015-11-01

As a result, five clades come out from phylogenetic reconstruction and in phylogenetic tree Barbus lacerta determined to be sister group of Barbus macedonicus, Barbus oligolepis and Barbus plebejus complex.

The phylogenetics of succession can guide restoration

DEFF Research Database (Denmark)

Shooner, Stephanie; Chisholm, Chelsea Lee; Davies, T. Jonathan

2015-01-01

Phylogenetic tools have increasingly been used in community ecology to describe the evolutionary relationships among co-occurring species. In studies of succession, such tools may allow us to identify the evolutionary lineages most suited for particular stages of succession and habitat...... rehabilitation. However, to date, these two applications have been largely separate. Here, we suggest that information on phylogenetic community structure might help to inform community restoration strategies following major disturbance. Our study examined phylogenetic patterns of succession based...... for species sorting along abiotic gradients (slope and aspect) on the mine sites that had been abandoned for the longest. Synthesis and applications. Understanding the trajectory of succession is critical for restoration efforts. Our results suggest that early colonizers represent a phylogenetically random...

Effects of Phylogenetic Tree Style on Student Comprehension

Science.gov (United States)

Dees, Jonathan Andrew

Phylogenetic trees are powerful tools of evolutionary biology that have become prominent across the life sciences. Consequently, learning to interpret and reason from phylogenetic trees is now an essential component of biology education. However, students often struggle to understand these diagrams, even after explicit instruction. One factor that has been observed to affect student understanding of phylogenetic trees is style (i.e., diagonal or bracket). The goal of this dissertation research was to systematically explore effects of style on student interpretations and construction of phylogenetic trees in the context of an introductory biology course. Before instruction, students were significantly more accurate with bracket phylogenetic trees for a variety of interpretation and construction tasks. Explicit instruction that balanced the use of diagonal and bracket phylogenetic trees mitigated some, but not all, style effects. After instruction, students were significantly more accurate for interpretation tasks involving taxa relatedness and construction exercises when using the bracket style. Based on this dissertation research and prior studies on style effects, I advocate for introductory biology instructors to use only the bracket style. Future research should examine causes of style effects and variables other than style to inform the development of research-based instruction that best supports student understanding of phylogenetic trees.

Bayesian models for comparative analysis integrating phylogenetic uncertainty

Directory of Open Access Journals (Sweden)

Villemereuil Pierre de

2012-06-01

Full Text Available Abstract Background Uncertainty in comparative analyses can come from at least two sources: a phylogenetic uncertainty in the tree topology or branch lengths, and b uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow and inflated significance in hypothesis testing (e.g. p-values will be too small. Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible

Bayesian models for comparative analysis integrating phylogenetic uncertainty

Science.gov (United States)

2012-01-01

Background Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for

Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.

Science.gov (United States)

Kooi, Thijs; van Ginneken, Bram; Karssemeijer, Nico; den Heeten, Ard

2017-03-01

It is estimated that 7% of women in the western world will develop palpable breast cysts in their lifetime. Even though cysts have been correlated with risk of developing breast cancer, many of them are benign and do not require follow-up. We develop a method to discriminate benign solitary cysts from malignant masses in digital mammography. We think a system like this can have merit in the clinic as a decision aid or complementary to specialized modalities. We employ a deep convolutional neural network (CNN) to classify cyst and mass patches. Deep CNNs have been shown to be powerful classifiers, but need a large amount of training data for which medical problems are often difficult to come by. The key contribution of this paper is that we show good performance can be obtained on a small dataset by pretraining the network on a large dataset of a related task. We subsequently investigate the following: (a) when a mammographic exam is performed, two different views of the same breast are recorded. We investigate the merit of combining the output of the classifier from these two views. (b) We evaluate the importance of the resolution of the patches fed to the network. (c) A method dubbed tissue augmentation is subsequently employed, where we extract normal tissue from normal patches and superimpose this onto the actual samples aiming for a classifier invariant to occluding tissue. (d) We combine the representation extracted using the deep CNN with our previously developed features. We show that using the proposed deep learning method, an area under the ROC curve (AUC) value of 0.80 can be obtained on a set of benign solitary cysts and malignant mass findings recalled in screening. We find that it works significantly better than our previously developed approach by comparing the AUC of the ROC using bootstrapping. By combining views, the results can be further improved, though this difference was not found to be significant. We find no significant difference between

Nucleotide diversity and phylogenetic relationships among ...

Indian Academy of Sciences (India)

Navya

2 attached at the base of tree as the diverging Iridaceae relative's lineage. Present study revealed that psbA-trnH region are useful in addressing questions of phylogenetic relationships among the Gladiolus cultivars, as these intergenic spacers are more variable and have more phylogenetically informative sites than the ...

Point estimates in phylogenetic reconstructions

OpenAIRE

Benner, Philipp; Bacak, Miroslav; Bourguignon, Pierre-Yves

2013-01-01

Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated pos...

A non-toxigenic but morphologically and phylogenetically distinct new species of Pseudo-nitzschia, P. sabit sp. nov. (Bacillariophyceae).

Science.gov (United States)

Teng, Sing Tung; Lim, Po Teen; Lim, Hong Chang; Rivera-Vilarelle, María; Quijano-Scheggia, Sonia; Takata, Yoshinobu; Quilliam, Michael A; Wolf, Matthias; Bates, Stephen S; Leaw, Chui Pin

2015-08-01

A new species of Pseudo-nitzschia (Bacillariophyceae) is described from plankton samples collected from Port Dickson (Malacca Strait, Malaysia) and Manzanillo Bay (Colima, Mexico). The species possesses a distinctive falcate cell valve, from which they form sickle-like colonies in both environmental samples and cultured strains. Detailed observation of frustules under TEM revealed ultrastructure that closely resembles P. decipiens, yet the new species differs by the valve shape and greater ranges of striae and poroid densities. The species is readily distinguished from the curve-shaped P. subcurvata by the presence of a central interspace. The morphological distinction is further supported by phylogenetic discrimination. We sequenced and analyzed the nuclear ribosomal RNA genes in the LSU and the second internal transcribed spacer, including its secondary structure, to infer the phylogenetic relationship of the new species with its closest relatives. The results revealed a distinct lineage of the new species, forming a sister cluster with its related species, P. decipiens and P. galaxiae, but not with P. subcurvata. We examined the domoic acid (DA) production of five cultured strains from Malaysia by Liquid chromatography-mass spectrometry (LC-MS), but they showed no detectable DA. Here, we present the taxonomic description of the vegetative cells, document the sexual reproduction, and detail the molecular phylogenetics of Pseudo-nitzschia sabit sp. nov. © 2015 Phycological Society of America.

Open Reading Frame Phylogenetic Analysis on the Cloud

Directory of Open Access Journals (Sweden)

Che-Lun Hung

2013-01-01

Full Text Available Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus.

Comparative evolutionary diversity and phylogenetic structure across multiple forest dynamics plots: a mega-phylogeny approach

Science.gov (United States)

Erickson, David L.; Jones, Frank A.; Swenson, Nathan G.; Pei, Nancai; Bourg, Norman A.; Chen, Wenna; Davies, Stuart J.; Ge, Xue-jun; Hao, Zhanqing; Howe, Robert W.; Huang, Chun-Lin; Larson, Andrew J.; Lum, Shawn K. Y.; Lutz, James A.; Ma, Keping; Meegaskumbura, Madhava; Mi, Xiangcheng; Parker, John D.; Fang-Sun, I.; Wright, S. Joseph; Wolf, Amy T.; Ye, W.; Xing, Dingliang; Zimmerman, Jess K.; Kress, W. John

2014-01-01

Forest dynamics plots, which now span longitudes, latitudes, and habitat types across the globe, offer unparalleled insights into the ecological and evolutionary processes that determine how species are assembled into communities. Understanding phylogenetic relationships among species in a community has become an important component of assessing assembly processes. However, the application of evolutionary information to questions in community ecology has been limited in large part by the lack of accurate estimates of phylogenetic relationships among individual species found within communities, and is particularly limiting in comparisons between communities. Therefore, streamlining and maximizing the information content of these community phylogenies is a priority. To test the viability and advantage of a multi-community phylogeny, we constructed a multi-plot mega-phylogeny of 1347 species of trees across 15 forest dynamics plots in the ForestGEO network using DNA barcode sequence data (rbcL, matK, and psbA-trnH) and compared community phylogenies for each individual plot with respect to support for topology and branch lengths, which affect evolutionary inference of community processes. The levels of taxonomic differentiation across the phylogeny were examined by quantifying the frequency of resolved nodes throughout. In addition, three phylogenetic distance (PD) metrics that are commonly used to infer assembly processes were estimated for each plot [PD, Mean Phylogenetic Distance (MPD), and Mean Nearest Taxon Distance (MNTD)]. Lastly, we examine the partitioning of phylogenetic diversity among community plots through quantification of inter-community MPD and MNTD. Overall, evolutionary relationships were highly resolved across the DNA barcode-based mega-phylogeny, and phylogenetic resolution for each community plot was improved when estimated within the context of the mega-phylogeny. Likewise, when compared with phylogenies for individual plots, estimates of

Characterization of Escherichia coli Phylogenetic Groups ...

African Journals Online (AJOL)

Background: Escherichia coli strains mainly fall into four phylogenetic groups (A, B1, B2, and D) and that virulent extra‑intestinal strains mainly belong to groups B2 and D. Aim: The aim was to determine the association between phylogenetic groups of E. coli causing extraintestinal infections (ExPEC) regarding the site of ...

Development of a multiplex real-time PCR assay for phylogenetic analysis of Uropathogenic Escherichia coli.

Science.gov (United States)

Hasanpour, Mojtaba; Najafi, Akram

2017-06-01

Uropathogenic Escherichia coli (UPEC) is among major pathogens causing 80-90% of all episodes of urinary tract infections (UTIs). Recently, E. coli strains are divided into eight main phylogenetic groups including A, B1, B2, C, D, E, F, and clade I. This study was aimed to develop a rapid, sensitive, and specific multiplex real time PCR method capable of detecting phylogenetic groups of E. coli strains. This study was carried out on E. coli strains (isolated from the patient with UTI) in which the presence of all seven target genes had been confirmed in our previous phylogenetic study. An EvaGreen-based singleplex and multiplex real-time PCR with melting curve analysis was designed for simultaneous detection and differentiation of these genes. The primers were selected mainly based on the production of amplicons with melting temperatures (T m ) ranging from 82°C to 93°C and temperature difference of more than 1.5°C between each peak.The multiplex real-time PCR assays that have been developed in the present study were successful in detecting the eight main phylogenetic groups. Seven distinct melting peaks were discriminated, with Tm value of 93±0.8 for arpA, 89.2±0.1for chuA, 86.5±0.1 for yjaA, 82.3±0.2 for TspE4C2, 87.8±0.1for trpAgpC, 85.4±0.6 for arpAgpE genes, and 91±0.5 for the internal control. To our knowledge, this study is the first melting curve-based real-time PCR assay developed for simultaneous and discrete detection of these seven target genes. Our findings showed that this assay has the potential to be a rapid, reliable and cost-effective alternative for routine phylotyping of E. coli strains. Copyright © 2017 Elsevier B.V. All rights reserved.

Visualizing phylogenetic tree landscapes.

Science.gov (United States)

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D

Abnormal hubs of white matter networks in the frontal-parieto circuit contribute to depression discrimination via pattern classification.

Science.gov (United States)

Qin, Jiaolong; Wei, Maobin; Liu, Haiyan; Chen, Jianhuai; Yan, Rui; Hua, Lingling; Zhao, Ke; Yao, Zhijian; Lu, Qing

2014-12-01

Previous studies had explored the diagnostic and prognostic value of the structural neuroimaging data of MDD and treated the whole brain voxels, the fractional anisotropy and the structural connectivity as classification features. To our best knowledge, no study examined the potential diagnostic value of the hubs of anatomical brain networks in MDD. The purpose of the current study was to provide an exploratory examination of the potential diagnostic and prognostic values of hubs of white matter brain networks in MDD discrimination and the corresponding impaired hub pattern via a multi-pattern analysis. We constructed white matter brain networks from 29 depressions and 30 healthy controls based on diffusion tensor imaging data, calculated nodal measures and identified hubs. Using these measures as features, two types of feature architectures were established, one only included hubs (HUB) and the other contained both hubs and non hubs. The support vector machine classifiers with Gaussian radial basis kernel were used after the feature selection. Moreover, the relative contribution of the features was estimated by means of the consensus features. Our results presented that the hubs (including the bilateral dorsolateral part of superior frontal gyrus, the left middle frontal gyrus, the bilateral middle temporal gyrus, and the bilateral inferior temporal gyrus) played an important role in distinguishing the depressions from healthy controls with the best accuracy of 83.05%. Moreover, most of the HUB consensus features located in the frontal-parieto circuit. These findings provided evidence that the hubs could be served as valuable potential diagnostic measure for MDD, and the hub-concentrated lesion distribution of MDD was primarily anchored within the frontal-parieto circuit. Copyright © 2014 Elsevier Inc. All rights reserved.

Topological variation in single-gene phylogenetic trees

OpenAIRE

Castresana, Jose

2007-01-01

A recent large-scale phylogenomic study has shown the great degree of topological variation that can be found among eukaryotic phylogenetic trees constructed from single genes, highlighting the problems that can be associated with gene sampling in phylogenetic studies.

Network Neutrality : A Survey of the Economic Literature

NARCIS (Netherlands)

Schuett, F.

2010-01-01

This paper reviews the small but growing economic literature on network neutrality. It considers a number of possible departures from network neutrality, in particular termination fees, second-degree price discrimination, and vertical foreclosure.

Interim Report on Multiple Sequence Alignments and TaqMan Signature Mapping to Phylogenetic Trees

Energy Technology Data Exchange (ETDEWEB)

Gardner, S; Jaing, C

2012-03-27

The goal of this project is to develop forensic genotyping assays for select agent viruses, addressing a significant capability gap for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the Taqman signature development for South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.

Sequence comparison and phylogenetic analysis of core gene of ...

African Journals Online (AJOL)

Phylogenetic analysis suggests that our sequences are clustered with sequences reported from Japan. This is the first phylogenetic analysis of HCV core gene from Pakistani population. Our sequences and sequences from Japan are grouped into same cluster in the phylogenetic tree. Sequence comparison and ...

PhyDesign: an online application for profiling phylogenetic informativeness

Directory of Open Access Journals (Sweden)

Townsend Jeffrey P

2011-05-01

Full Text Available Abstract Background The rapid increase in number of sequenced genomes for species across of the tree of life is revealing a diverse suite of orthologous genes that could potentially be employed to inform molecular phylogenetic studies that encompass broader taxonomic sampling. Optimal usage of this diversity of loci requires user-friendly tools to facilitate widespread cost-effective locus prioritization for phylogenetic sampling. The Townsend (2007 phylogenetic informativeness provides a unique empirical metric for guiding marker selection. However, no software or automated methodology to evaluate sequence alignments and estimate the phylogenetic informativeness metric has been available. Results Here, we present PhyDesign, a platform-independent online application that implements the Townsend (2007 phylogenetic informativeness analysis, providing a quantitative prediction of the utility of loci to solve specific phylogenetic questions. An easy-to-use interface facilitates uploading of alignments and ultrametric trees to calculate and depict profiles of informativeness over specified time ranges, and provides rankings of locus prioritization for epochs of interest. Conclusions By providing these profiles, PhyDesign facilitates locus prioritization increasing the efficiency of sequencing for phylogenetic purposes compared to traditional studies with more laborious and low capacity screening methods, as well as increasing the accuracy of phylogenetic studies. Together with a manual and sample files, the application is freely accessible at http://phydesign.townsend.yale.edu.

Barcoding success as a function of phylogenetic relatedness in Viburnum, a clade of woody angiosperms

Directory of Open Access Journals (Sweden)

Clement Wendy L

2012-05-01

Full Text Available Abstract Background The chloroplast genes matK and rbcL have been proposed as a “core” DNA barcode for identifying plant species. Published estimates of successful species identification using these loci (70-80% may be inflated because they may have involved comparisons among distantly related species within target genera. To assess the ability of the proposed two-locus barcode to discriminate closely related species, we carried out a hierarchically structured set of comparisons within Viburnum, a clade of woody angiosperms containing ca. 170 species (some 70 of which are currently used in horticulture. For 112 Viburnum species, we evaluated rbcL + matK, as well as the chloroplast regions rpl32-trnL, trnH-psbA, trnK, and the nuclear ribosomal internal transcribed spacer region (nrITS. Results At most, rbcL + matK could discriminate 53% of all Viburnum species, with only 18% of the comparisons having genetic distances >1%. When comparisons were progressively restricted to species within major Viburnum subclades, there was a significant decrease in both the discriminatory power and the genetic distances. trnH-psbA and nrITS show much higher levels of variation and potential discriminatory power, and their use in plant barcoding should be reconsidered. As barcoding has often been used to discriminate species within local areas, we also compared Viburnum species within two regions, Japan and Mexico and Central America. Greater success in discriminating among the Japanese species reflects the deeper evolutionary history of Viburnum in that area, as compared to the recent radiation of a single clade into the mountains of Latin America. Conclusions We found very low levels of discrimination among closely related species of Viburnum, and low levels of variation in the proposed barcoding loci may limit success within other clades of long-lived woody plants. Inclusion of the supplementary barcodes trnH-psbA and nrITS increased discrimination rates but

Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods

Directory of Open Access Journals (Sweden)

Leandro de Jesus Benevides

Full Text Available Abstract Apolipoprotein E (apo E is a human glycoprotein with 299 amino acids, and it is a major component of very low density lipoproteins (VLDL and a group of high-density lipoproteins (HDL. Phylogenetic studies are important to clarify how various apo E proteins are related in groups of organisms and whether they evolved from a common ancestor. Here, we aimed at performing a phylogenetic study on apo E carrying organisms. We employed a classical and robust method, such as Maximum Likelihood (ML, and compared the results using a more recent approach based on complex networks. Thirty-two apo E amino acid sequences were downloaded from NCBI. A clear separation could be observed among three major groups: mammals, fish and amphibians. The results obtained from ML method, as well as from the constructed networks showed two different groups: one with mammals only (C1 and another with fish (C2, and a single node with the single sequence available for an amphibian. The accordance in results from the different methods shows that the complex networks approach is effective in phylogenetic studies. Furthermore, our results revealed the conservation of apo E among animal groups.

Phylogenetic Structure of Foliar Spectral Traits in Tropical Forest Canopies

Directory of Open Access Journals (Sweden)

Kelly M. McManus

2016-02-01

Full Text Available The Spectranomics approach to tropical forest remote sensing has established a link between foliar reflectance spectra and the phylogenetic composition of tropical canopy tree communities vis-à-vis the taxonomic organization of biochemical trait variation. However, a direct relationship between phylogenetic affiliation and foliar reflectance spectra of species has not been established. We sought to develop this relationship by quantifying the extent to which underlying patterns of phylogenetic structure drive interspecific variation among foliar reflectance spectra within three Neotropical canopy tree communities with varying levels of soil fertility. We interpreted the resulting spectral patterns of phylogenetic signal in the context of foliar biochemical traits that may contribute to the spectral-phylogenetic link. We utilized a multi-model ensemble to elucidate trait-spectral relationships, and quantified phylogenetic signal for spectral wavelengths and traits using Pagel’s lambda statistic. Foliar reflectance spectra showed evidence of phylogenetic influence primarily within the visible and shortwave infrared spectral regions. These regions were also selected by the multi-model ensemble as those most important to the quantitative prediction of several foliar biochemical traits. Patterns of phylogenetic organization of spectra and traits varied across sites and with soil fertility, indicative of the complex interactions between the environmental and phylogenetic controls underlying patterns of biodiversity.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Ling-Li Zeng

2018-04-01

Full Text Available Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, f

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

Science.gov (United States)

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Reaction Time and Self-Report Psychopathological Assessment: Convergent and Discriminant Validity.

Science.gov (United States)

Holden, Ronald R.; Fekken, G. Cynthia

The processing of incoming psychological information along the network, or schemata, of self-knowledge was studied to determine the convergent and discriminant validity of the patterns of schemata-specific response latencies. Fifty-three female and 52 male university students completed the Basic Personality Inventory (BPI). BPI scales assess…

Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution.

Science.gov (United States)

Kendall, Michelle; Colijn, Caroline

2016-10-01

Evolutionary relationships are frequently described by phylogenetic trees, but a central barrier in many fields is the difficulty of interpreting data containing conflicting phylogenetic signals. We present a metric-based method for comparing trees which extracts distinct alternative evolutionary relationships embedded in data. We demonstrate detection and resolution of phylogenetic uncertainty in a recent study of anole lizards, leading to alternate hypotheses about their evolutionary relationships. We use our approach to compare trees derived from different genes of Ebolavirus and find that the VP30 gene has a distinct phylogenetic signature composed of three alternatives that differ in the deep branching structure. phylogenetics, evolution, tree metrics, genetics, sequencing. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Molecular Phylogenetics: Mathematical Framework and Unsolved Problems

Science.gov (United States)

Xia, Xuhua

Phylogenetic relationship is essential in dating evolutionary events, reconstructing ancestral genes, predicting sites that are important to natural selection, and, ultimately, understanding genomic evolution. Three categories of phylogenetic methods are currently used: the distance-based, the maximum parsimony, and the maximum likelihood method. Here, I present the mathematical framework of these methods and their rationales, provide computational details for each of them, illustrate analytically and numerically the potential biases inherent in these methods, and outline computational challenges and unresolved problems. This is followed by a brief discussion of the Bayesian approach that has been recently used in molecular phylogenetics.

Population data and phylogenetic structure of Han population from Jiangsu province of China on GlobalFiler STR loci.

Science.gov (United States)

Adnan, Atif; Zhan, Xiaoni; Kasim, Kadirya; Rakha, Allah; Xin, Xing Jia

2018-03-02

Forensic statistical parameters based on allelic frequencies of commonly used short tandem repeats were estimated for the Han population of Jiangsu province from P.R. China. The 6-dye GlobalFiler™ PCR amplification kit incorporates 21 autosomal STRs, providing reliable DNA typing results with enhanced the power of discrimination. Here, we analyzed the GlobalFiler™ STR loci in 516 unrelated individuals from Jiangsu Han population. A total of 256 alleles were observed ranging between 5 and 35.2 repeat units, and SE33 showed the greatest power of discrimination (34 alleles) in Jiangsu Han population. Most of the loci were found to be in the Hardy-Weinberg equilibrium after the Bonferroni correction with the exception of D3S1358. The combined power of exclusion (CPE) was 0.999999996353609, and the combined match probability (CMP) was 3.64 × 10 -25 . Phylogenetic parameters including pairwise genetic distances showed that Han population living in Jiangsu had closest genetic relationship with other East Asian populations. The present study provides precise reference database for forensic applications and population genetic studies.

Phylogenetic community structure: temporal variation in fish assemblage

OpenAIRE

Santorelli, Sergio; Magnusson, William; Ferreira, Efrem; Caramaschi, Erica; Zuanon, Jansen; Amadio, Sidnéia

2014-01-01

Hypotheses about phylogenetic relationships among species allow inferences about the mechanisms that affect species coexistence. Nevertheless, most studies assume that phylogenetic patterns identified are stable over time. We used data on monthly samples of fish from a single lake over 10 years to show that the structure in phylogenetic assemblages varies over time and conclusions depend heavily on the time scale investigated. The data set was organized in guild structures and temporal scales...

The application of sparse estimation of covariance matrix to quadratic discriminant analysis.

Science.gov (United States)

Sun, Jiehuan; Zhao, Hongyu

2015-02-18

Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) across different diseases has been observed in many genomics studies, which suggests that LDA and its variations may be suboptimal for disease classifications. However, it is not clear whether considering differing genetic networks across diseases can improve classification in genomics studies. We propose a sparse version of Quadratic Discriminant Analysis (SQDA) to explicitly consider the differences of the genetic networks across diseases. Both simulation and real data analysis are performed to compare the performance of SQDA with six commonly used classification methods. SQDA provides more accurate classification results than other methods for both simulated and real data. Our method should prove useful for classification in genomics studies and other research settings, where covariances differ among classes.

Pulse duration discriminator

International Nuclear Information System (INIS)

Kosakovskij, L.F.

1980-01-01

Basic circuits of a discriminator for discrimination of pulses with the duration greater than the preset one, and of a multifunctional discriminator allowing to discriminate pulses with the duration greater (tsub(p)>tsub(s)) and lesser (tsub(p) tsub(s) and with the duration tsub(p) [ru

Discrimination of complex human behavior by pigeons (Columba livia and humans.

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Muhammad A J Qadri

Full Text Available The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors ("martial arts" vs. "Indian dance". Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species.

Social networks and employment in India

OpenAIRE

Tushar K. Nandi

2010-01-01

We investigate the influence of social networks on employment. Using data from India, we estimate the effect of caste based social networks on employment. We use a methodology that allows us to control for several omitted variable biases that often confound network effect. Our results indicate that caste based social networks are important determinant of employment in India. The implication of our findings is that a policy of positive discrimination in labour market for disadvantaged caste is...

Virulence, serotype and phylogenetic groups of diarrhoeagenic ...

African Journals Online (AJOL)

Dr DADIE Thomas

2014-02-17

Feb 17, 2014 ... The virulence, serotype and phylogenetic traits of diarrhoeagenic Escherichia coli were detected in 502 strains isolated during digestive infections. Molecular detection of the target virulence genes, rfb gene of operon O and phylogenetic grouping genes Chua, yjaA and TSPE4.C2 was performed.

["Long-branch Attraction" artifact in phylogenetic reconstruction].

Science.gov (United States)

Li, Yi-Wei; Yu, Li; Zhang, Ya-Ping

2007-06-01

Phylogenetic reconstruction among various organisms not only helps understand their evolutionary history but also reveal several fundamental evolutionary questions. Understanding of the evolutionary relationships among organisms establishes the foundation for the investigations of other biological disciplines. However, almost all the widely used phylogenetic methods have limitations which fail to eliminate systematic errors effectively, preventing the reconstruction of true organismal relationships. "Long-branch Attraction" (LBA) artifact is one of the most disturbing factors in phylogenetic reconstruction. In this review, the conception and analytic method as well as the avoidance strategy of LBA were summarized. In addition, several typical examples were provided. The approach to avoid and resolve LBA artifact has been discussed.

Neural dynamics of motion processing and speed discrimination.

Science.gov (United States)

Chey, J; Grossberg, S; Mingolla, E

1998-09-01

A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-turned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1-->MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that has been used to simulate how global motion capture occurs, and how spatial attention is drawn to moving forms. It provides a computational foundation for an emerging neural theory of 3-D form and motion perception.

From Gene Trees to a Dated Allopolyploid Network: Insights from the Angiosperm Genus Viola (Violaceae)

Science.gov (United States)

Marcussen, Thomas; Heier, Lise; Brysting, Anne K.; Oxelman, Bengt; Jakobsen, Kjetill S.

2015-01-01

Allopolyploidization accounts for a significant fraction of speciation events in many eukaryotic lineages. However, existing phylogenetic and dating methods require tree-like topologies and are unable to handle the network-like phylogenetic relationships of lineages containing allopolyploids. No explicit framework has so far been established for evaluating competing network topologies, and few attempts have been made to date phylogenetic networks. We used a four-step approach to generate a dated polyploid species network for the cosmopolitan angiosperm genus Viola L. (Violaceae Batch.). The genus contains ca 600 species and both recent (neo-) and more ancient (meso-) polyploid lineages distributed over 16 sections. First, we obtained DNA sequences of three low-copy nuclear genes and one chloroplast region, from 42 species representing all 16 sections. Second, we obtained fossil-calibrated chronograms for each nuclear gene marker. Third, we determined the most parsimonious multilabeled genome tree and its corresponding network, resolved at the section (not the species) level. Reconstructing the “correct” network for a set of polyploids depends on recovering all homoeologs, i.e., all subgenomes, in these polyploids. Assuming the presence of Viola subgenome lineages that were not detected by the nuclear gene phylogenies (“ghost subgenome lineages”) significantly reduced the number of inferred polyploidization events. We identified the most parsimonious network topology from a set of five competing scenarios differing in the interpretation of homoeolog extinctions and lineage sorting, based on (i) fewest possible ghost subgenome lineages, (ii) fewest possible polyploidization events, and (iii) least possible deviation from expected ploidy as inferred from available chromosome counts of the involved polyploid taxa. Finally, we estimated the homoploid and polyploid speciation times of the most parsimonious network. Homoploid speciation times were estimated by

Using targeted enrichment of nuclear genes to increase phylogenetic resolution in the neotropical rain forest genus Inga (Leguminosae: Mimosoideae

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James A Nicholls

2015-09-01

Full Text Available Evolutionary radiations are prominent and pervasive across many plant lineages in diverse geographical and ecological settings; in neotropical rainforests there is growing evidence suggesting that a significant fraction of species richness is the result of recent radiations. Understanding the evolutionary trajectories and mechanisms underlying these radiations demands much greater phylogenetic resolution than is currently available for these groups. The neotropical tree genus Inga (Leguminosae is a good example, with ~300 extant species and a crown age of 2-10 MY, yet over 6kb of plastid and nuclear DNA sequence data gives only poor phylogenetic resolution among species. Here we explore the use of larger-scale nuclear gene data obtained though targeted enrichment to increase phylogenetic resolution within Inga. Transcriptome data from three Inga species were used to select 264 nuclear loci for targeted enrichment and sequencing. Following quality control to remove probable paralogs from these sequence data, the final dataset comprised 259,313 bases from 194 loci for 24 accessions representing 22 Inga species and an outgroup (Zygia. Bayesian phylogenies reconstructed using either all loci concatenated or a subset of 60 loci in a gene-tree/species-tree approach yielded highly resolved phylogenies. We used coalescent approaches to show that the same targeted enrichment data also have significant power to discriminate among alternative within-species population histories in the widespread species I. umbellifera. In either application, targeted enrichment simplifies the informatics challenge of identifying orthologous loci associated with de novo genome sequencing. We conclude that targeted enrichment provides the large volumes of phylogenetically-informative sequence data required to resolve relationships within recent plant species radiations, both at the species level and for within-species phylogeographic studies.

Phylogenetic analysis of Tibetan mastiffs based on mitochondrial hypervariable region I.

Science.gov (United States)

Ren, Zhanjun; Chen, Huiling; Yang, Xuejiao; Zhang, Chengdong

2017-03-01

Recently, the number of Tibetan mastiffs, which is a precious germplasm resource and cultural heritage, is decreasing sharply. Therefore, the genetic diversity of Tibetan mastiffs needs to be studied to clarify its phylogenetics relationships and lay the foundation for resource protection, rational development and utilization of Tibetan mastiffs. We sequenced hypervariable region I of mitochondrial DNA (mtDNA) of 110 individuals from Tibet region and Gansu province. A total of 12 polymorphic sites were identified which defined eight haplotypes of which H4 and H8 were unique to Tibetan population with H8 being identified first. The haplotype diversity (Hd: 0.808), nucleotide diversity (Pi: 0.603%), the average number of nucleotide difference (K: 3.917) of Tibetan mastiffs from Gansu were higher than those from Tibet region (Hd: 0.794; Pi: 0.589%; K: 3.831), which revealed higher genetic diversity in Gansu. In terms of total population, the genetic variation was low. The median-joining network and phylogenetic tree based on the mtDNA hypervariable region I showed that Tibetan mastiffs originated from grey wolves, as the other domestic dogs and had different history of maternal origin. The mismatch distribution analysis and neutrality tests indicated that Tibetan mastiffs were in genetic equilibrium or in a population decline.

Phylogenetically Acquired Representations and Evolutionary Algorithms.

OpenAIRE

Wozniak , Adrianna

2006-01-01

First, we explain why Genetic Algorithms (GAs), inspired by the Modern Synthesis, do not accurately model biological evolution, being rather an artificial version of artificial, rather than natural selection. Being focused on optimisation, we propose two improvements of GAs, with the aim to successfully generate adapted, desired behaviour. The first one concerns phylogenetic grounding of meaning, a way to avoid the Symbol Grounding Problem. We give a definition of Phylogenetically Acquired Re...

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

KAUST Repository

Kamiran, Faisal

2012-11-18

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in

Perceived Discrimination in LGBTIQ Discourse: A Typology of Verbal Discrimination

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Sol Rojas Lizana

2014-08-01

Full Text Available New within the field of Discourse Analysis, Perceived Discrimination (PD is the study of discourse that focuses on the perspective of the victims of discrimination. This article explores the experiences of verbal discrimination as reported by eighteen LGBTIQ participants during semi-structured, co-constructed interviews. Data were classified in order to develop a taxonomy of discrimination based on Mellor’s (2003, 2004. This taxonomy foregrounds two types of discrimination: verbal and behavioural. In this paper, I exemplify the forms of verbal discrimination encountered and offer an analysis of the discourse used in the construction of the experiences and of the effects reported. The results show that verbal discrimination is an overt phenomenon and that participants are stressed by the ever present possibility of facing it. Verbal discrimination is mainly triggered by a perceived transgression to the normalised standards of people’s behaviour, movements and look in a heterosexist society. It presents three subtypes: name calling, abuse and remarks. These subtypes are described through the analysis of keywords, effects and expressions (such as faggot, gay, dyke, queer, the pronoun ‘it’, religious comments and other remarks. The type of discrimination used was associated with the level of acquaintance perpetrators have with the experiencers; that is, name calling was used by people unknown to the victims while abuse and remarks by acquaintances and family members. Participants resorted to several discursive strategies to convey their intentions. They used mitigation strategies when wanting to minimize the experience, hedging and repetition were used for emphasis, and to convey urgency and pervasiveness. Metaphorical expressions related to internal or external injuries were also used to express the powerful effect of verbal discrimination on people.

Molecular Phylogenetic: Organism Taxonomy Method Based on Evolution History

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N.L.P Indi Dharmayanti

2011-03-01

Full Text Available Phylogenetic is described as taxonomy classification of an organism based on its evolution history namely its phylogeny and as a part of systematic science that has objective to determine phylogeny of organism according to its characteristic. Phylogenetic analysis from amino acid and protein usually became important area in sequence analysis. Phylogenetic analysis can be used to follow the rapid change of a species such as virus. The phylogenetic evolution tree is a two dimensional of a species graphic that shows relationship among organisms or particularly among their gene sequences. The sequence separation are referred as taxa (singular taxon that is defined as phylogenetically distinct units on the tree. The tree consists of outer branches or leaves that represents taxa and nodes and branch represent correlation among taxa. When the nucleotide sequence from two different organism are similar, they were inferred to be descended from common ancestor. There were three methods which were used in phylogenetic, namely (1 Maximum parsimony, (2 Distance, and (3 Maximum likehoood. Those methods generally are applied to construct the evolutionary tree or the best tree for determine sequence variation in group. Every method is usually used for different analysis and data.

YBYRÁ facilitates comparison of large phylogenetic trees.

Science.gov (United States)

Machado, Denis Jacob

2015-07-01

The number and size of tree topologies that are being compared by phylogenetic systematists is increasing due to technological advancements in high-throughput DNA sequencing. However, we still lack tools to facilitate comparison among phylogenetic trees with a large number of terminals. The "YBYRÁ" project integrates software solutions for data analysis in phylogenetics. It comprises tools for (1) topological distance calculation based on the number of shared splits or clades, (2) sensitivity analysis and automatic generation of sensitivity plots and (3) clade diagnoses based on different categories of synapomorphies. YBYRÁ also provides (4) an original framework to facilitate the search for potential rogue taxa based on how much they affect average matching split distances (using MSdist). YBYRÁ facilitates comparison of large phylogenetic trees and outperforms competing software in terms of usability and time efficiency, specially for large data sets. The programs that comprises this toolkit are written in Python, hence they do not require installation and have minimum dependencies. The entire project is available under an open-source licence at http://www.ib.usp.br/grant/anfibios/researchSoftware.html .

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

Science.gov (United States)

Qian, Kun; Zhou, Huixin; Wang, Bingjian; Song, Shangzhen; Zhao, Dong

2017-11-01

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.

Disentangling the phylogenetic and ecological components of spider phenotypic variation.

Science.gov (United States)

Gonçalves-Souza, Thiago; Diniz-Filho, José Alexandre Felizola; Romero, Gustavo Quevedo

2014-01-01

An understanding of how the degree of phylogenetic relatedness influences the ecological similarity among species is crucial to inferring the mechanisms governing the assembly of communities. We evaluated the relative importance of spider phylogenetic relationships and ecological niche (plant morphological variables) to the variation in spider body size and shape by comparing spiders at different scales: (i) between bromeliads and dicot plants (i.e., habitat scale) and (ii) among bromeliads with distinct architectural features (i.e., microhabitat scale). We partitioned the interspecific variation in body size and shape into phylogenetic (that express trait values as expected by phylogenetic relationships among species) and ecological components (that express trait values independent of phylogenetic relationships). At the habitat scale, bromeliad spiders were larger and flatter than spiders associated with the surrounding dicots. At this scale, plant morphology sorted out close related spiders. Our results showed that spider flatness is phylogenetically clustered at the habitat scale, whereas it is phylogenetically overdispersed at the microhabitat scale, although phylogenic signal is present in both scales. Taken together, these results suggest that whereas at the habitat scale selective colonization affect spider body size and shape, at fine scales both selective colonization and adaptive evolution determine spider body shape. By partitioning the phylogenetic and ecological components of phenotypic variation, we were able to disentangle the evolutionary history of distinct spider traits and show that plant architecture plays a role in the evolution of spider body size and shape. We also discussed the relevance in considering multiple scales when studying phylogenetic community structure.

Phylogenetic system and zoogeography of the Plecoptera.

Science.gov (United States)

Zwick, P

2000-01-01

Information about the phylogenetic relationships of Plecoptera is summarized. The few characters supporting monophyly of the order are outlined. Several characters of possible significance for the search for the closest relatives of the stoneflies are discussed, but the sister-group of the order remains unknown. Numerous characters supporting the presently recognized phylogenetic system of Plecoptera are presented, alternative classifications are discussed, and suggestions for future studies are made. Notes on zoogeography are appended. The order as such is old (Permian fossils), but phylogenetic relationships and global distribution patterns suggest that evolution of the extant suborders started with the breakup of Pangaea. There is evidence of extensive recent speciation in all parts of the world.

Deep learning in color: towards automated quark/gluon jet discrimination

International Nuclear Information System (INIS)

Komiske, Patrick T.; Metodiev, Eric M.; Schwartz, Matthew D.

2017-01-01

Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. Here, to establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark and gluon jets better than observables designed by physicists. Our approach builds upon the paradigm that a jet can be treated as an image, with intensity given by the local calorimeter deposits. We supplement this construction by adding color to the images, with red, green and blue intensities given by the transverse momentum in charged particles, transverse momentum in neutral particles, and pixel-level charged particle counts. Overall, the deep networks match or outperform traditional jet variables. We also find that, while various simulations produce different quark and gluon jets, the neural networks are surprisingly insensitive to these differences, similar to traditional observables. This suggests that the networks can extract robust physical information from imperfect simulations.

Pulse-width discriminators

International Nuclear Information System (INIS)

Budyashov, Yu.G.; Grebenyuk, V.M.; Zinov, V.G.

1978-01-01

A pulse duration discriminator is described which is intended for processing signals from multilayer scintillators. The basic elements of the scintillator are: an input gate, a current generator, an integrating capacitor, a Schmidt trigger and an anticoincidence circuit. The basic circuit of the discriminator and its time diagrams explaining its operating are given. The discriminator is based on microcircuits. Pulse duration discrimination threshold changes continuously from 20 to 100 ns, while its amplitude threshold changes within 20 to 100 mV. The temperature instability of discrimination thresholds (both in pulse width and in amplitude) is better than 0.1 per cent/deg C

The best of both worlds: Phylogenetic eigenvector regression and mapping

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José Alexandre Felizola Diniz Filho

2015-09-01

Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

Genomic and phylogenetic characterization of luminous bacteria symbiotic with the deep-sea fish Chlorophthalmus albatrossis (Aulopiformes: Chlorophthalmidae).

Science.gov (United States)

Dunlap, Paul V; Ast, Jennifer C

2005-02-01

Bacteria forming light-organ symbiosis with deep-sea chlorophthalmid fishes (Aulopiformes: Chlorophthalmidae) are considered to belong to the species Photobacterium phosphoreum. The identification of these bacteria as P. phosphoreum, however, was based exclusively on phenotypic traits, which may not discriminate between phenetically similar but evolutionarily distinct luminous bacteria. Therefore, to test the species identification of chlorophthalmid symbionts, we carried out a genomotypic (repetitive element palindromic PCR genomic profiling) and phylogenetic analysis on strains isolated from the perirectal light organ of Chlorophthalmus albatrossis. Sequence analysis of the 16S rRNA gene of 10 strains from 5 fish specimens placed these bacteria in a cluster related to but phylogenetically distinct from the type strain of P. phosphoreum, ATCC 11040(T), and the type strain of Photobacterium iliopiscarium, ATCC 51760(T). Analysis of gyrB resolved the C. albatrossis strains as a strongly supported clade distinct from P. phosphoreum and P. iliopiscarium. Genomic profiling of 109 strains from the 5 C. albatrossis specimens revealed a high level of similarity among strains but allowed identification of genomotypically different types from each fish. Representatives of each type were then analyzed phylogenetically, using sequence of the luxABFE genes. As with gyrB, analysis of luxABFE resolved the C. albatrossis strains as a robustly supported clade distinct from P. phosphoreum. Furthermore, other strains of luminous bacteria reported as P. phosphoreum, i.e., NCIMB 844, from the skin of Merluccius capensis (Merlucciidae), NZ-11D, from the light organ of Nezumia aequalis (Macrouridae), and pjapo.1.1, from the light organ of Physiculus japonicus (Moridae), grouped phylogenetically by gyrB and luxABFE with the C. albatrossis strains, not with ATCC 11040(T). These results demonstrate that luminous bacteria symbiotic with C. albatrossis, together with certain other strains of

Phylogenetic Analyses of Armillaria Reveal at Least 15 Phylogenetic Lineages in China, Seven of Which Are Associated with Cultivated Gastrodia elata.

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Ting Guo

Full Text Available Fungal species of Armillaria, which can act as plant pathogens and/or symbionts of the Chinese traditional medicinal herb Gastrodia elata ("Tianma", are ecologically and economically important and have consequently attracted the attention of mycologists. However, their taxonomy has been highly dependent on morphological characterization and mating tests. In this study, we phylogenetically analyzed Chinese Armillaria samples using the sequences of the internal transcribed spacer region, translation elongation factor-1 alpha gene and beta-tubulin gene. Our data revealed at least 15 phylogenetic lineages of Armillaria from China, of which seven were newly discovered and two were recorded from China for the first time. Fourteen Chinese biological species of Armillaria, which were previously defined based on mating tests, could be assigned to the 15 phylogenetic lineages identified herein. Seven of the 15 phylogenetic lineages were found to be disjunctively distributed in different continents of the Northern Hemisphere, while eight were revealed to be endemic to certain continents. In addition, we found that seven phylogenetic lineages of Armillaria were used for the cultivation of Tianma, only two of which had been recorded to be associated with Tianma previously. We also illustrated that G. elata f. glauca ("Brown Tianma" and G. elata f. elata ("Red Tianma", two cultivars of Tianma grown in different regions of China, form symbiotic relationships with different phylogenetic lineages of Armillaria. These findings should aid the development of Tianma cultivation in China.

Phylogenetic relationships within and among Brassica species from ...

African Journals Online (AJOL)

Consequently, two potentially susceptible B. napus accessions were identified. The high polymorphic information content (PIC) and number of phylogenetically informative bands established RAPD as a useful tool for phylogenetic reconstruction, quantification of genetic diversity for conservation, cultivar classification and ...

A neural network to predict symptomatic lung injury

International Nuclear Information System (INIS)

Munley, M.T.; Lo, J.Y.

1999-01-01

A nonlinear neural network that simultaneously uses pre-radiotherapy (RT) biological and physical data was developed to predict symptomatic lung injury. The input data were pre-RT pulmonary function, three-dimensional treatment plan doses and demographics. The output was a single value between 0 (asymptomatic) and 1 (symptomatic) to predict the likelihood that a particular patient would become symptomatic. The network was trained on data from 97 patients for 400 iterations with the goal to minimize the mean-squared error. Statistical analysis was performed on the resulting network to determine the model's accuracy. Results from the neural network were compared with those given by traditional linear discriminate analysis and the dose-volume histogram reduction (DVHR) scheme of Kutcher. Receiver-operator characteristic (ROC) analysis was performed on the resulting network which had Az=0.833±0.04. (Az is the area under the ROC curve.) Linear discriminate multivariate analysis yielded an Az=0.813±0.06. The DVHR method had Az=0.521±0.08. The network was also used to rank the significance of the input variables. Future studies will be conducted to improve network accuracy and to include functional imaging data. (author)

Temporal Discrimination: Mechanisms and Relevance to Adult-Onset Dystonia

Directory of Open Access Journals (Sweden)

Antonella Conte

2017-11-01

Full Text Available Temporal discrimination is the ability to determine that two sequential sensory stimuli are separated in time. For any individual, the temporal discrimination threshold (TDT is the minimum interval at which paired sequential stimuli are perceived as being asynchronous; this can be assessed, with high test–retest and inter-rater reliability, using a simple psychophysical test. Temporal discrimination is disordered in a number of basal ganglia diseases including adult-onset dystonia, of which the two most common phenotypes are cervical dystonia and blepharospasm. The causes of adult-onset focal dystonia are unknown; genetic, epigenetic, and environmental factors are relevant. Abnormal TDTs in adult-onset dystonia are associated with structural and neurophysiological changes considered to reflect defective inhibitory interneuronal processing within a network which includes the superior colliculus, basal ganglia, and primary somatosensory cortex. It is hypothesized that abnormal temporal discrimination is a mediational endophenotype and, when present in unaffected relatives of patients with adult-onset dystonia, indicates non-manifesting gene carriage. Using the mediational endophenotype concept, etiological factors in adult-onset dystonia may be examined including (i the role of environmental exposures in disease penetrance and expression; (ii sexual dimorphism in sex ratios at age of onset; (iii the pathogenesis of non-motor symptoms of adult-onset dystonia; and (iv subcortical mechanisms in disease pathogenesis.

Visualising very large phylogenetic trees in three dimensional hyperbolic space

Directory of Open Access Journals (Sweden)

Liberles David A

2004-04-01

Full Text Available Abstract Background Common existing phylogenetic tree visualisation tools are not able to display readable trees with more than a few thousand nodes. These existing methodologies are based in two dimensional space. Results We introduce the idea of visualising phylogenetic trees in three dimensional hyperbolic space with the Walrus graph visualisation tool and have developed a conversion tool that enables the conversion of standard phylogenetic tree formats to Walrus' format. With Walrus, it becomes possible to visualise and navigate phylogenetic trees with more than 100,000 nodes. Conclusion Walrus enables desktop visualisation of very large phylogenetic trees in 3 dimensional hyperbolic space. This application is potentially useful for visualisation of the tree of life and for functional genomics derivatives, like The Adaptive Evolution Database (TAED.

Genetic diversity and molecular evolution of Naga King Chili inferred from internal transcribed spacer sequence of nuclear ribosomal DNA.

Science.gov (United States)

Kehie, Mechuselie; Kumaria, Suman; Devi, Khumuckcham Sangeeta; Tandon, Pramod

2016-02-01

Sequences of the Internal Transcribed Spacer (ITS1-5.8S-ITS2) of nuclear ribosomal DNAs were explored to study the genetic diversity and molecular evolution of Naga King Chili. Our study indicated the occurrence of nucleotide polymorphism and haplotypic diversity in the ITS regions. The present study demonstrated that the variability of ITS1 with respect to nucleotide diversity and sequence polymorphism exceeded that of ITS2. Sequence analysis of 5.8S gene revealed a much conserved region in all the accessions of Naga King Chili. However, strong phylogenetic information of this species is the distinct 13 bp deletion in the 5.8S gene which discriminated Naga King Chili from the rest of the Capsicum sp. Neutrality test results implied a neutral variation, and population seems to be evolving at drift-mutation equilibrium and free from directed selection pressure. Furthermore, mismatch analysis showed multimodal curve indicating a demographic equilibrium. Phylogenetic relationships revealed by Median Joining Network (MJN) analysis denoted a clear discrimination of Naga King Chili from its closest sister species (Capsicum chinense and Capsicum frutescens). The absence of star-like network of haplotypes suggested an ancient population expansion of this chili.

Eddy Current Flaw Characterization Using Neural Networks

International Nuclear Information System (INIS)

Song, S. J.; Park, H. J.; Shin, Y. K.

1998-01-01

Determination of location, shape and size of a flaw from its eddy current testing signal is one of the fundamental issues in eddy current nondestructive evaluation of steam generator tubes. Here, we propose an approach to this problem; an inversion of eddy current flaw signal using neural networks trained by finite element model-based synthetic signatures. Total 216 eddy current signals from four different types of axisymmetric flaws in tubes are generated by finite element models of which the accuracy is experimentally validated. From each simulated signature, total 24 eddy current features are extracted and among them 13 features are finally selected for flaw characterization. Based on these features, probabilistic neural networks discriminate flaws into four different types according to the location and the shape, and successively back propagation neural networks determine the size parameters of the discriminated flaw

Reconstruction of phylogenetic relationships in dermatomycete genus Trichophyton Malmsten 1848 based on ribosomal internal transcribed spacer region, partial 28S rRNA and beta-tubulin genes sequences.

Science.gov (United States)

Pchelin, Ivan M; Zlatogursky, Vasily V; Rudneva, Mariya V; Chilina, Galina A; Rezaei-Matehkolaei, Ali; Lavnikevich, Dmitry M; Vasilyeva, Natalya V; Taraskina, Anastasia E

2016-09-01

Trichophyton spp. are important causative agents of superficial mycoses. The phylogeny of the genus and accurate strain identification, based on the ribosomal ITS region sequencing, are still under development. The present work is aimed at (i) inferring the genus phylogeny from partial ITS, LSU and BT2 sequences (ii) description of ribosomal ITS region polymorphism in 15 strains of Trichophyton interdigitale. We performed DNA sequence-based species identification and phylogenetic analysis on 48 strains belonging to the genus Trichophyton. Phylogenetic relationships were inferred by maximum likelihood and Bayesian methods on concatenated ITS, LSU and BT2 sequences. Ribosomal ITS region polymorphisms were assessed directly on the alignment. By phylogenetic reconstruction, we reveal major anthropophilic and zoophilic species clusters in the genus Trichophyton. We describe several sequences of the ITS region of T. interdigitale, which do not fit in the traditional polymorphism scheme and propose emendations in this scheme for discrimination between ITS sequence types in T. interdigitale. The new polymorphism scheme will allow inclusion of a wider spectrum of isolates while retaining its explanatory power. This scheme was also found to be partially congruent with NTS typing technique. © 2016 Blackwell Verlag GmbH.

Climate-driven extinctions shape the phylogenetic structure of temperate tree floras.

Science.gov (United States)

Eiserhardt, Wolf L; Borchsenius, Finn; Plum, Christoffer M; Ordonez, Alejandro; Svenning, Jens-Christian

2015-03-01

When taxa go extinct, unique evolutionary history is lost. If extinction is selective, and the intrinsic vulnerabilities of taxa show phylogenetic signal, more evolutionary history may be lost than expected under random extinction. Under what conditions this occurs is insufficiently known. We show that late Cenozoic climate change induced phylogenetically selective regional extinction of northern temperate trees because of phylogenetic signal in cold tolerance, leading to significantly and substantially larger than random losses of phylogenetic diversity (PD). The surviving floras in regions that experienced stronger extinction are phylogenetically more clustered, indicating that non-random losses of PD are of increasing concern with increasing extinction severity. Using simulations, we show that a simple threshold model of survival given a physiological trait with phylogenetic signal reproduces our findings. Our results send a strong warning that we may expect future assemblages to be phylogenetically and possibly functionally depauperate if anthropogenic climate change affects taxa similarly. © 2015 John Wiley & Sons Ltd/CNRS.

Increased phylogenetic resolution using target enrichment in Rubus

Science.gov (United States)

Phylogenetic analyses in Rubus L. have been challenging due to polyploidy, hybridization, and apomixis within the genus. Wide morphological diversity occurs within and between species, contributing to challenges at lower and higher systematic levels. Phylogenetic inferences to date have been based o...

Phylogenetic relationships of African sunbird-like warblers: Moho ...

African Journals Online (AJOL)

Phylogenetic relationships of African sunbird-like warblers: Moho ( Hypergerus atriceps ), Green Hylia ( Hylia prasina ) and Tit-hylia ( Pholidornis rushiae ) ... different points in avian evolution reduces the phylogenetic signal in molecular sequence data, making difficult the reconstruction of relationships among taxa resulting ...

Convergent evolution of gene networks by single-gene duplications in higher eukaryotes

OpenAIRE

Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

2004-01-01

By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix–loop–helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks e...

Interpreting the universal phylogenetic tree

Science.gov (United States)

Woese, C. R.

2000-01-01

The universal phylogenetic tree not only spans all extant life, but its root and earliest branchings represent stages in the evolutionary process before modern cell types had come into being. The evolution of the cell is an interplay between vertically derived and horizontally acquired variation. Primitive cellular entities were necessarily simpler and more modular in design than are modern cells. Consequently, horizontal gene transfer early on was pervasive, dominating the evolutionary dynamic. The root of the universal phylogenetic tree represents the first stage in cellular evolution when the evolving cell became sufficiently integrated and stable to the erosive effects of horizontal gene transfer that true organismal lineages could exist.

Discrimination of multilocus sequence typing-based Campylobacter jejuni subgroups by MALDI-TOF mass spectrometry.

Science.gov (United States)

Zautner, Andreas Erich; Masanta, Wycliffe Omurwa; Tareen, Abdul Malik; Weig, Michael; Lugert, Raimond; Groß, Uwe; Bader, Oliver

2013-11-07

Campylobacter jejuni, the most common bacterial pathogen causing gastroenteritis, shows a wide genetic diversity. Previously, we demonstrated by the combination of multi locus sequence typing (MLST)-based UPGMA-clustering and analysis of 16 genetic markers that twelve different C. jejuni subgroups can be distinguished. Among these are two prominent subgroups. The first subgroup contains the majority of hyperinvasive strains and is characterized by a dimeric form of the chemotaxis-receptor Tlp7(m+c). The second has an extended amino acid metabolism and is characterized by the presence of a periplasmic asparaginase (ansB) and gamma-glutamyl-transpeptidase (ggt). Phyloproteomic principal component analysis (PCA) hierarchical clustering of MALDI-TOF based intact cell mass spectrometry (ICMS) spectra was able to group particular C. jejuni subgroups of phylogenetic related isolates in distinct clusters. Especially the aforementioned Tlp7(m+c)(+) and ansB+/ ggt+ subgroups could be discriminated by PCA. Overlay of ICMS spectra of all isolates led to the identification of characteristic biomarker ions for these specific C. jejuni subgroups. Thus, mass peak shifts can be used to identify the C. jejuni subgroup with an extended amino acid metabolism. Although the PCA hierarchical clustering of ICMS-spectra groups the tested isolates into a different order as compared to MLST-based UPGMA-clustering, the isolates of the indicator-groups form predominantly coherent clusters. These clusters reflect phenotypic aspects better than phylogenetic clustering, indicating that the genes corresponding to the biomarker ions are phylogenetically coupled to the tested marker genes. Thus, PCA clustering could be an additional tool for analyzing the relatedness of bacterial isolates.

Seismic Discrimination of Earthquakes and Explosions, with Application to the Southwestern United States

Science.gov (United States)

1979-03-22

multi-station discriminants than by those based on network averages. In spite of this situ - ation, average a posteriori probabilities were sometimes...Technology, Pasadena, California. Allen, C. R., L. T. Silver, and F. G. Stehi (1960). Agua Blanca fault - a major transverse structure of northern Baja

Hard and soft age discrimination: the dual nature of workplace discrimination.

Science.gov (United States)

Stypinska, Justyna; Turek, Konrad

2017-03-01

The paper concentrates on the problem of age discrimination in the labour market and the way it can be conceptualised and measured in a multi-disciplinary way. The approach proposed here combines two understandings of age discrimination-a sociological and legal one, what allows for a fuller and expanded understanding of ageism in the workplace. At the heart of the study is a survey carried out in Poland with a sample of 1000 men and women aged 45-65 years. The study takes a deeper and innovative look into the issue of age discrimination in employment. Confirmatory factor analysis with WLSMV estimation and logistic regressions were used to test the hypotheses. The study shows that age discrimination in labour market can take on different forms: hard and soft, where the hard type of age discrimination mirrors the legally prohibited types of behaviours and those which relate to the actual decisions of employers which can impact on the employee's career development. The soft discrimination corresponds with those occurrences, which are not inscribed in the legal system per se, are occurring predominantly in the interpersonal sphere, but can nevertheless have negative consequences. Soft discrimination was experienced more often (28.6% of respondents) than hard discrimination (15.7%) with higher occurrences among women, persons in precarious job situation or residents of urban areas. The role of education was not confirmed to influence the levels of perceived age discrimination.

Utilization of complete chloroplast genomes for phylogenetic studies

NARCIS (Netherlands)

Ramlee, Shairul Izan Binti

2016-01-01

Chloroplast DNA sequence polymorphisms are a primary source of data in many plant phylogenetic studies. The chloroplast genome is relatively conserved in its evolution making it an ideal molecule to retain phylogenetic signals. The chloroplast genome is also largely, but not completely, free from

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

NARCIS (Netherlands)

Kamiran, F.; Zliobaite, I.; Calders, T.G.K.

2013-01-01

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train

Estimating phylogenetic trees from genome-scale data.

Science.gov (United States)

Liu, Liang; Xi, Zhenxiang; Wu, Shaoyuan; Davis, Charles C; Edwards, Scott V

2015-12-01

The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data. © 2015 New York Academy of Sciences.

Revealing effective classifiers through network comparison

Science.gov (United States)

Gallos, Lazaros K.; Fefferman, Nina H.

2014-11-01

The ability to compare complex systems can provide new insight into the fundamental nature of the processes captured, in ways that are otherwise inaccessible to observation. Here, we introduce the n-tangle method to directly compare two networks for structural similarity, based on the distribution of edge density in network subgraphs. We demonstrate that this method can efficiently introduce comparative analysis into network science and opens the road for many new applications. For example, we show how the construction of a “phylogenetic tree” across animal taxa according to their social structure can reveal commonalities in the behavioral ecology of the populations, or how students create similar networks according to the University size. Our method can be expanded to study many additional properties, such as network classification, changes during time evolution, convergence of growth models, and detection of structural changes during damage.

New weighting methods for phylogenetic tree reconstruction using multiple loci.

Science.gov (United States)

Misawa, Kazuharu; Tajima, Fumio

2012-08-01

Efficient determination of evolutionary distances is important for the correct reconstruction of phylogenetic trees. The performance of the pooled distance required for reconstructing a phylogenetic tree can be improved by applying large weights to appropriate distances for reconstructing phylogenetic trees and small weights to inappropriate distances. We developed two weighting methods, the modified Tajima-Takezaki method and the modified least-squares method, for reconstructing phylogenetic trees from multiple loci. By computer simulations, we found that both of the new methods were more efficient in reconstructing correct topologies than the no-weight method. Hence, we reconstructed hominoid phylogenetic trees from mitochondrial DNA using our new methods, and found that the levels of bootstrap support were significantly increased by the modified Tajima-Takezaki and by the modified least-squares method.

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

Science.gov (United States)

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231

Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

Science.gov (United States)

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.

On the information content of discrete phylogenetic characters.

Science.gov (United States)

Bordewich, Magnus; Deutschmann, Ina Maria; Fischer, Mareike; Kasbohm, Elisa; Semple, Charles; Steel, Mike

2017-12-16

Phylogenetic inference aims to reconstruct the evolutionary relationships of different species based on genetic (or other) data. Discrete characters are a particular type of data, which contain information on how the species should be grouped together. However, it has long been known that some characters contain more information than others. For instance, a character that assigns the same state to each species groups all of them together and so provides no insight into the relationships of the species considered. At the other extreme, a character that assigns a different state to each species also conveys no phylogenetic signal. In this manuscript, we study a natural combinatorial measure of the information content of an individual character and analyse properties of characters that provide the maximum phylogenetic information, particularly, the number of states such a character uses and how the different states have to be distributed among the species or taxa of the phylogenetic tree.

DendroPy: a Python library for phylogenetic computing.

Science.gov (United States)

Sukumaran, Jeet; Holder, Mark T

2010-06-15

DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy's data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines. The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).

Handling conditional discrimination

NARCIS (Netherlands)

Zliobaite, I.; Kamiran, F.; Calders, T.G.K.

2011-01-01

Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free with respect to a given sensitive attribute, e.g., gender. Existing techniques that deal with this problem aim at removing all discrimination

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

Community Phylogenetics: Assessing Tree Reconstruction Methods and the Utility of DNA Barcodes

Science.gov (United States)

Boyle, Elizabeth E.; Adamowicz, Sarah J.

2015-01-01

Studies examining phylogenetic community structure have become increasingly prevalent, yet little attention has been given to the influence of the input phylogeny on metrics that describe phylogenetic patterns of co-occurrence. Here, we examine the influence of branch length, tree reconstruction method, and amount of sequence data on measures of phylogenetic community structure, as well as the phylogenetic signal (Pagel’s λ) in morphological traits, using Trichoptera larval communities from Churchill, Manitoba, Canada. We find that model-based tree reconstruction methods and the use of a backbone family-level phylogeny improve estimations of phylogenetic community structure. In addition, trees built using the barcode region of cytochrome c oxidase subunit I (COI) alone accurately predict metrics of phylogenetic community structure obtained from a multi-gene phylogeny. Input tree did not alter overall conclusions drawn for phylogenetic signal, as significant phylogenetic structure was detected in two body size traits across input trees. As the discipline of community phylogenetics continues to expand, it is important to investigate the best approaches to accurately estimate patterns. Our results suggest that emerging large datasets of DNA barcode sequences provide a vast resource for studying the structure of biological communities. PMID:26110886

A genotype network reveals homoplastic cycles of convergent evolution in influenza A (H3N2) haemagglutinin.

Science.gov (United States)

Wagner, Andreas

2014-07-07

Networks of evolving genotypes can be constructed from the worldwide time-resolved genotyping of pathogens like influenza viruses. Such genotype networks are graphs where neighbouring vertices (viral strains) differ in a single nucleotide or amino acid. A rich trove of network analysis methods can help understand the evolutionary dynamics reflected in the structure of these networks. Here, I analyse a genotype network comprising hundreds of influenza A (H3N2) haemagglutinin genes. The network is rife with cycles that reflect non-random parallel or convergent (homoplastic) evolution. These cycles also show patterns of sequence change characteristic for strong and local evolutionary constraints, positive selection and mutation-limited evolution. Such cycles would not be visible on a phylogenetic tree, illustrating that genotype network analysis can complement phylogenetic analyses. The network also shows a distinct modular or community structure that reflects temporal more than spatial proximity of viral strains, where lowly connected bridge strains connect different modules. These and other organizational patterns illustrate that genotype networks can help us study evolution in action at an unprecedented level of resolution. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Consequences of recombination on traditional phylogenetic analysis

DEFF Research Database (Denmark)

Schierup, M H; Hein, J

2000-01-01

We investigate the shape of a phylogenetic tree reconstructed from sequences evolving under the coalescent with recombination. The motivation is that evolutionary inferences are often made from phylogenetic trees reconstructed from population data even though recombination may well occur (mt......DNA or viral sequences) or does occur (nuclear sequences). We investigate the size and direction of biases when a single tree is reconstructed ignoring recombination. Standard software (PHYLIP) was used to construct the best phylogenetic tree from sequences simulated under the coalescent with recombination....... With recombination present, the length of terminal branches and the total branch length are larger, and the time to the most recent common ancestor smaller, than for a tree reconstructed from sequences evolving with no recombination. The effects are pronounced even for small levels of recombination that may...

Phylogenetic relationships of the lancelets of the genus ...

African Journals Online (AJOL)

phylogenetic relationships of the Branchiostoma lancelets from South (Xiamen) and North (Qingdao and Rizhao) China, and phylogenetic trees constructed also included the existing data from Japanese waters. The genetic distances of the lancelets between South and North China averaged 0.19, 0.21, and 0.17 based on ...

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

OpenAIRE

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning ...

Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

Science.gov (United States)

Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

2017-08-01

The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

Racial discrimination, gender discrimination, and substance abuse among Latina/os nationwide.

Science.gov (United States)

Otiniano Verissimo, Angie Denisse; Gee, Gilbert C; Ford, Chandra L; Iguchi, Martin Y

2014-01-01

This study investigates the relationship between discrimination and substance abuse among Latina/os, and further examines whether this relationship differs by gender and type of discrimination. Analyses focus on the Latina/o respondents (n = 1,039 men; n = 1,273 women) from the National Latino and Asian American Study carried out from 2002-2003. Outcomes were alcohol abuse and drug abuse measured using DSM-IV definitions and criteria. Additional covariates included immigrant characteristics and demographics. Analyses were completed using gender-stratified multinomial logistic regression. Men reported more discrimination (39.6% vs. 30.3%) and had higher prevalence of alcohol abuse (16.5% vs. 4.5%) and drug abuse (9.5% vs. 2.3%) than women. Discrimination was significantly associated with increased risk of alcohol abuse for women and increased risk of drug abuse for men. Men and women also varied in the types of discrimination (e.g., racial vs. gender) reported, and in the associations between these types of discrimination and substance abuse. These data indicate that discrimination is associated with different substance abuse outcomes between genders. Future research should consider the mechanisms that explain these differences.

Enumerating all maximal frequent subtrees in collections of phylogenetic trees.

Science.gov (United States)

Deepak, Akshay; Fernández-Baca, David

2014-01-01

A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees.

Automatic interpretation of F-18-FDG brain PET using artificial neural network: discrimination of medial and lateral temporal lobe epilepsy

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Sung; Lee, Dong Soo; Kim, Seok Ki; Park, Kwang Suk; Lee, Sang Kun; Chung, June Key; Lee, Myung Chul [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of)

2004-06-01

We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). We studied brain F-18-FDG PET images of 113 epilepsy patients surgically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptions (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 81 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier. Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE.

Automatic interpretation of F-18-FDG brain PET using artificial neural network: discrimination of medial and lateral temporal lobe epilepsy

International Nuclear Information System (INIS)

Lee, Jae Sung; Lee, Dong Soo; Kim, Seok Ki; Park, Kwang Suk; Lee, Sang Kun; Chung, June Key; Lee, Myung Chul

2004-01-01

We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). We studied brain F-18-FDG PET images of 113 epilepsy patients surgically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptions (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 81 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier. Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE

Bacillus subtilis Protects Public Goods by Extending Kin Discrimination to Closely Related Species.

Science.gov (United States)

Lyons, Nicholas A; Kolter, Roberto

2017-07-05

Kin discrimination systems are found in numerous communal contexts like multicellularity and are theorized to prevent exploitation of cooperative behaviors. The kin discrimination system in Bacillus subtilis differs from most other such systems because it excludes nonkin cells rather than including kin cells. Because nonkin are the target of the system, B. subtilis can potentially distinguish degrees of nonkin relatedness, not just kin versus nonkin. We examined this by testing a large strain collection of diverse Bacillus species against B. subtilis in different multicellular contexts. The effects of kin discrimination extend to nearby species, as the other subtilis clade species were treated with the same antagonism as nonkin. Species in the less-related pumilus clade started to display varied phenotypes but were mostly still discriminated against, while cereus clade members and beyond were no longer subject to kin discrimination. Seeking a reason why other species are perceived as antagonistic nonkin, we tested the ability of B. subtilis to steal communally produced surfactant from these species. We found that the species treated as nonkin were the only ones that made a surfactant that B. subtilis could utilize and that nonkin antagonism prevented such stealing when the two strains were mixed. The nonkin exclusion kin discrimination method thus allows effective protection of the cooperative behaviors prevalent in multicellularity while still permitting interactions with more distant species that are not a threat. IMPORTANCE Multicellular systems like bacterial biofilms and swarms rely on cooperative behaviors that could be undermined by exploitative invaders. Discriminating kin from nonkin is one way to help guard against such exploitation but has thus far been examined only intraspecifically, so the phylogenetic range of this important trait is unknown. We tested whether Bacillus subtilis treats other species as nonkin by testing a single strain against a

Structure versus time in the evolutionary diversification of avian carotenoid metabolic networks.

Science.gov (United States)

Morrison, Erin S; Badyaev, Alexander V

2018-05-01

Historical associations of genes and proteins are thought to delineate pathways available to subsequent evolution; however, the effects of past functional involvements on contemporary evolution are rarely quantified. Here, we examined the extent to which the structure of a carotenoid enzymatic network persists in avian evolution. Specifically, we tested whether the evolution of carotenoid networks was most concordant with phylogenetically structured expansion from core reactions of common ancestors or with subsampling of biochemical pathway modules from an ancestral network. We compared structural and historical associations in 467 carotenoid networks of extant and ancestral species and uncovered the overwhelming effect of pre-existing metabolic network structure on carotenoid diversification over the last 50 million years of avian evolution. Over evolutionary time, birds repeatedly subsampled and recombined conserved biochemical modules, which likely maintained the overall structure of the carotenoid metabolic network during avian evolution. These findings explain the recurrent convergence of evolutionary distant species in carotenoid metabolism and weak phylogenetic signal in avian carotenoid evolution. Remarkable retention of an ancient metabolic structure throughout extensive and prolonged ecological diversification in avian carotenoid metabolism illustrates a fundamental requirement of organismal evolution - historical continuity of a deterministic network that links past and present functional associations of its components. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Discrimination of transgenic soybean seeds by terahertz spectroscopy

Science.gov (United States)

Liu, Wei; Liu, Changhong; Chen, Feng; Yang, Jianbo; Zheng, Lei

2016-10-01

Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of glyphosate-resistant and conventional soybean seeds and their hybrid descendants was examined by terahertz time-domain spectroscopy system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM) and PCA-back propagation neural network (PCA-BPNN) models with the first and second derivative and standard normal variate (SNV) transformation pre-treatments were applied to classify soybean seeds based on genotype. Results demonstrated clear differences among glyphosate-resistant, hybrid descendants and conventional non-transformed soybean seeds could easily be visualized with an excellent classification (accuracy was 88.33% in validation set) using the LS-SVM and the spectra with SNV pre-treatment. The results indicated that THz spectroscopy techniques together with chemometrics would be a promising technique to distinguish transgenic soybean seeds from non-transformed seeds with high efficiency and without any major sample preparation.

Comparative phylogenetic analysis of intergenic spacers and small ...

African Journals Online (AJOL)

The phylogenetic analysis of test isolates included assessment of variation in sequences and length of IGS and SSU-rRNA genes with reference to 16 different microsporidian sequences. The results proved that IGS sequences have more variation than SSU-rRNA gene sequences. Analysis of phylogenetic trees reveal that ...

LABOR DISCRIMINATION IN BULGARIA

Directory of Open Access Journals (Sweden)

Vyara Slavyanska

2017-03-01

Full Text Available Labor discrimination is a phenomenon with very serious social and economic consequences, which has increased actuality and importance in Bulgaria nowadays. Because of the high price of discrimination, building effective anti-discrimination legislation occupies a special place in the policy of the European Union. Despite the European directives, the presence of anti-discrimination legislation and the broadly declared anti-discrimination inclinations in our country, these are absolutely not enough for providing environment of equality, with a climate of respect and tolerance to the differences. It turns out that certain groups are definitely victims of labor discrimination. In this connection the present article consecutively identifies these groups, as well as the reasons for their discrimination, underlining the necessity and benefits of the integration of the different.

What are the best concentric descriptors for complex networks?

International Nuclear Information System (INIS)

Costa, Luciano da Fontoura; Andrade, Roberto Fernandes Silva

2007-01-01

This work reviews several concentric measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erdoes-Renyi, Barabasi-Albert, Watts-Strogatz, as well as a geographical type of network. Progressive randomizations of the geographical model have also been considered. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two-dimensions, with the traditional clustering coefficient, concentric clustering coefficient and neighborhood clustering coefficient being particularly effective. Interestingly, the average shortest path length and concentric node degrees contributed little for the separation of the four network models

What are the best concentric descriptors for complex networks?

Energy Technology Data Exchange (ETDEWEB)

Costa, Luciano da Fontoura [Instituto de Fisica de Sao Carlos, Universidade de Sao Paulo, Sao Carlos, SP, PO Box 369, 13560-970 (Brazil); Andrade, Roberto Fernandes Silva [Instituto de Fisica, Universidade Federal da Bahia, Salvador, Bahia, 40210-340 (Brazil)

2007-09-15

This work reviews several concentric measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erdoes-Renyi, Barabasi-Albert, Watts-Strogatz, as well as a geographical type of network. Progressive randomizations of the geographical model have also been considered. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two-dimensions, with the traditional clustering coefficient, concentric clustering coefficient and neighborhood clustering coefficient being particularly effective. Interestingly, the average shortest path length and concentric node degrees contributed little for the separation of the four network models.

Maximum parsimony, substitution model, and probability phylogenetic trees.

Science.gov (United States)

Weng, J F; Thomas, D A; Mareels, I

2011-01-01

The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.

Towards an integrated phylogenetic classification of the Tremellomycetes.

Science.gov (United States)

Liu, X-Z; Wang, Q-M; Göker, M; Groenewald, M; Kachalkin, A V; Lumbsch, H T; Millanes, A M; Wedin, M; Yurkov, A M; Boekhout, T; Bai, F-Y

2015-06-01

Families and genera assigned to Tremellomycetes have been mainly circumscribed by morphology and for the yeasts also by biochemical and physiological characteristics. This phenotype-based classification is largely in conflict with molecular phylogenetic analyses. Here a phylogenetic classification framework for the Tremellomycetes is proposed based on the results of phylogenetic analyses from a seven-genes dataset covering the majority of tremellomycetous yeasts and closely related filamentous taxa. Circumscriptions of the taxonomic units at the order, family and genus levels recognised were quantitatively assessed using the phylogenetic rank boundary optimisation (PRBO) and modified general mixed Yule coalescent (GMYC) tests. In addition, a comprehensive phylogenetic analysis on an expanded LSU rRNA (D1/D2 domains) gene sequence dataset covering as many as available teleomorphic and filamentous taxa within Tremellomycetes was performed to investigate the relationships between yeasts and filamentous taxa and to examine the stability of undersampled clades. Based on the results inferred from molecular data and morphological and physiochemical features, we propose an updated classification for the Tremellomycetes. We accept five orders, 17 families and 54 genera, including seven new families and 18 new genera. In addition, seven families and 17 genera are emended and one new species name and 185 new combinations are proposed. We propose to use the term pro tempore or pro tem. in abbreviation to indicate the species names that are temporarily maintained.

An efficient and extensible approach for compressing phylogenetic trees

KAUST Repository

Matthews, Suzanne J; Williams, Tiffani L

2011-01-01

Background: Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend

Conus pennaceus : a phylogenetic analysis of the Mozambican ...

African Journals Online (AJOL)

The genus Conus has over 500 species and is the most species-rich taxon of marine invertebrates. Based on mitochondrial DNA, this study focuses on the phylogenetics of Conus, particularly the pennaceus complex collected along the Mozambican coast. Phylogenetic trees based on both the 16S and the 12S ribosomal ...

Decorrelated Jet Substructure Tagging using Adversarial Neural Networks

CERN Multimedia

CERN. Geneva

2017-01-01

We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass. This reduces the impact of systematic uncertainties in background modeling while enhancing signal purity, resulting in improved discovery significance relative to existing taggers. The network is trained using an adversarial strategy, resulting in a tagger that learns to balance classification accuracy with decorrelation. As a benchmark scenario, we consider the case where large-radius jets originating from a boosted Z' decay are discriminated from a background of nonresonant quark and gluon jets. We show that in the presence of systematic uncertainties on the background rate, our adversarially-trained, decorrelated tagger considerably outperforms a conventionally trained neural network, despite having a slightly worse signal-background separation power. We generalize the adversarial training technique to include a paramet...

Set discrimination of quantum states

International Nuclear Information System (INIS)

Zhang Shengyu; Ying Mingsheng

2002-01-01

We introduce a notion of set discrimination, which is an interesting extension of quantum state discrimination. A state is secretly chosen from a number of quantum states, which are partitioned into some disjoint sets. A set discrimination is required to identify which set the given state belongs to. Several essential problems are addressed in this paper, including the condition of perfect set discrimination, unambiguous set discrimination, and in the latter case, the efficiency of the discrimination. This generalizes some important results on quantum state discrimination in the literature. A combination of state and set discrimination and the efficiency are also studied

Trophic phylogenetics: evolutionary influences on body size, feeding, and species associations in grassland arthropods.

Science.gov (United States)

Lind, Eric M; Vincent, John B; Weiblen, George D; Cavender-Bares, Jeannine; Borer, Elizabeth T

2015-04-01

Contemporary animal-plant interactions such as herbivory are widely understood to be shaped by evolutionary history. Yet questions remain about the role of plant phylogenetic diversity in generating and maintaining herbivore diversity, and whether evolutionary relatedness of producers might predict the composition of consumer communities. We tested for evidence of evolutionary associations among arthropods and the plants on which they were found, using phylogenetic analysis of naturally occurring arthropod assemblages sampled from a plant-diversity manipulation experiment. Considering phylogenetic relationships among more than 900 arthropod consumer taxa and 29 plant species in the experiment, we addressed several interrelated questions. First, our results support the hypothesis that arthropod functional traits such as body size and trophic role are phylogenetically conserved in community ecological samples. Second, herbivores tended to cooccur with closer phylogenetic relatives than would be expected at random, whereas predators and parasitoids did not show phylogenetic association patterns. Consumer specialization, as measured by association through time with monocultures of particular host plant species, showed significant phylogenetic signal, although the. strength of this association varied among plant species. Polycultures of phylogenetically dissimilar plant species supported more phylogenetically dissimilar consumer communities than did phylogenetically similar polycultures. Finally, we separated the effects of plant species richness and relatedness in predicting the phylogenetic distribution of the arthropod assemblages in this experiment. The phylogenetic diversity of plant communities predicted the phylogenetic diversity of herbivore communities even after accounting for plant species richness. The phylogenetic diversity of secondary consumers differed by guild, with predator phylogenetic diversity responding to herbivore relatedness, while parasitoid

Self-organizing networks for extracting jet features

International Nuclear Information System (INIS)

Loennblad, L.; Peterson, C.; Pi, H.; Roegnvaldsson, T.

1991-01-01

Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b.c. and light quarks. (orig.)

Discrimination and delusional ideation.

Science.gov (United States)

Janssen, I; Hanssen, M; Bak, M; Bijl, R V; de Graaf, R; Vollebergh, W; McKenzie, K; van Os, J

2003-01-01

In the UK and The Netherlands, people with high rates of psychosis are chronically exposed to discrimination. To test whether perceived discrimination is associated longitudinally with onset of psychosis. A 3-year prospective study of cohorts with no history of psychosis and differential rates of reported discrimination on the basis of age, gender, disability, appearance, skin colour or ethnicity and sexual orientation was conducted in the Dutch general population (n=4076). The main outcome was onset of psychotic symptoms (delusions and hallucinations). The rate of delusional ideation was 0.5% (n=19) in those who did not report discrimination, 0.9% (n=4) in those who reported discrimination in one domain, and 2.7% (n=3) in those who reported discrimination in more than one domain (exact P=0.027). This association remained after adjustment for possible confounders. No association was found between baseline discrimination and onset of hallucinatory experiences. Perceived discrimination may induce delusional ideation and thus contribute to the high observed rates of psychotic disorder in exposed minority populations.

Genetic variation and phylogenetic relationship analysis of Jatropha curcas L. inferred from nrDNA ITS sequences.

Science.gov (United States)

Guo, Guo-Ye; Chen, Fang; Shi, Xiao-Dong; Tian, Yin-Shuai; Yu, Mao-Qun; Han, Xue-Qin; Yuan, Li-Chun; Zhang, Ying

2016-01-01

Genetic variation and phylogenetic relationships among 102 Jatropha curcas accessions from Asia, Africa, and the Americas were assessed using the internal transcribed spacer region of nuclear ribosomal DNA (nrDNA ITS). The average G+C content (65.04%) was considerably higher than the A+T (34.96%) content. The estimated genetic diversity revealed moderate genetic variation. The pairwise genetic divergences (GD) between haplotypes were evaluated and ranged from 0.000 to 0.017, suggesting a higher level of genetic differentiation in Mexican accessions than those of other regions. Phylogenetic relationships and intraspecific divergence were inferred by Bayesian inference (BI), maximum parsimony (MP), and median joining (MJ) network analysis and were generally resolved. The J. curcas accessions were consistently divided into three lineages, groups A, B, and C, which demonstrated distant geographical isolation and genetic divergence between American accessions and those from other regions. The MJ network analysis confirmed that Central America was the possible center of origin. The putative migration route suggested that J. curcas was distributed from Mexico or Brazil, via Cape Verde and then split into two routes. One route was dispersed to Spain, then migrated to China, eventually spreading to southeastern Asia, while the other route was dispersed to Africa, via Madagascar and migrated to China, later spreading to southeastern Asia. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Enumerating all maximal frequent subtrees in collections of phylogenetic trees

Science.gov (United States)

2014-01-01

Background A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. Results We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Conclusions Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees. PMID:25061474

Phylogenetic fields through time: temporal dynamics of geographical co-occurrence and phylogenetic structure within species ranges.

Science.gov (United States)

Villalobos, Fabricio; Carotenuto, Francesco; Raia, Pasquale; Diniz-Filho, José Alexandre F

2016-04-05

Species co-occur with different sets of other species across their geographical distribution, which can be either closely or distantly related. Such co-occurrence patterns and their phylogenetic structure within individual species ranges represent what we call the species phylogenetic fields (PFs). These PFs allow investigation of the role of historical processes--speciation, extinction and dispersal--in shaping species co-occurrence patterns, in both extinct and extant species. Here, we investigate PFs of large mammalian species during the last 3 Myr, and how these correlate with trends in diversification rates. Using the fossil record, we evaluate species' distributional and co-occurrence patterns along with their phylogenetic structure. We apply a novel Bayesian framework on fossil occurrences to estimate diversification rates through time. Our findings highlight the effect of evolutionary processes and past climatic changes on species' distributions and co-occurrences. From the Late Pliocene to the Recent, mammal species seem to have responded in an individualistic manner to climate changes and diversification dynamics, co-occurring with different sets of species from different lineages across their geographical ranges. These findings stress the difficulty of forecasting potential effects of future climate changes on biodiversity. © 2016 The Author(s).

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

Directory of Open Access Journals (Sweden)

Min-Joo Kang

Full Text Available A novel intrusion detection system (IDS using a deep neural network (DNN is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN, therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN bus.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

Science.gov (United States)

Kang, Min-Joo; Kang, Je-Won

2016-01-01

A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

Identifying Jets Using Artifical Neural Networks

Science.gov (United States)

Rosand, Benjamin; Caines, Helen; Checa, Sofia

2017-09-01

We investigate particle jet interactions with the Quark Gluon Plasma (QGP) using artificial neural networks modeled on those used in computer image recognition. We create jet images by binning jet particles into pixels and preprocessing every image. We analyzed the jets with a Multi-layered maxout network and a convolutional network. We demonstrate each network's effectiveness in differentiating simulated quenched jets from unquenched jets, and we investigate the method that the network uses to discriminate among different quenched jet simulations. Finally, we develop a greater understanding of the physics behind quenched jets by investigating what the network learnt as well as its effectiveness in differentiating samples. Yale College Freshman Summer Research Fellowship in the Sciences and Engineering.

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.

Science.gov (United States)

Puhl, R M; Andreyeva, T; Brownell, K D

2008-06-01

Limited data are available on the prevalence and patterns of body weight discrimination from representative samples. This study examined experiences of weight/height discrimination in a nationally representative sample of US adults and compared their prevalence and patterns with discrimination experiences based on race and gender. Data were from the National Survey of Midlife Development in the United States, a 1995-1996 community-based survey of English-speaking adults aged 25-74 (N=2290). Reported experiences of weight/height discrimination included a variety of institutional settings and interpersonal relationships. Multivariate regression analyses were used to predict weight/height discrimination controlling for sociodemographic characteristics and body weight status. The prevalence of weight/height discrimination ranged from 5% among men to 10% among women, but these average percentages obscure the much higher risk of weight discrimination among heavier individuals (40% for adults with body mass index (BMI) of 35 and above). Younger individuals with a higher BMI had a particularly high risk of weight/height discrimination regardless of their race, education and weight status. Women were at greater risk for weight/height discrimination than men, especially women with a BMI of 30-35 who were three times more likely to report weight/height discrimination compared to male peers of a similar weight. Weight/height discrimination is prevalent in American society and is relatively close to reported rates of racial discrimination, particularly among women. Both institutional forms of weight/height discrimination (for example, in employment settings) and interpersonal mistreatment due to weight/height (for example, being called names) were common, and in some cases were even more prevalent than discrimination due to gender and race.

Remote interactions on two distributed quantum systems: nonlocal unambiguous quantum-state discrimination

International Nuclear Information System (INIS)

Chen Libing; Jin Ruibo; Lu Hong

2008-01-01

Remote quantum-state discrimination is a critical step for the implementation of quantum communication network and distributed quantum computation. We present a protocol for remotely implementing the unambiguous discrimination between nonorthogonal states using quantum entanglements, local operations, and classical communications. This protocol consists of a remote generalized measurement described by a positive operator valued measurement (POVM). We explicitly construct the required remote POVM. The remote POVM can be realized by performing a nonlocal controlled-rotation operation on two spatially separated qubits, one is an ancillary qubit and the other is the qubit which is encoded by two nonorthogonal states to be distinguished, and a conventional local Von Neumann orthogonal measurement on the ancilla. The particular pair of states that can be remotely and unambiguously distinguished is specified by the state of the ancilla. The probability of successful discrimination is not optimal for all admissible pairs. However, for some subset it can be very close to an optimal value in an ordinary local POVM

Depressive Symptoms among Latino Sexual Minority Men and Latina Transgender Women in a New Settlement State: The Role of Perceived Discrimination

Directory of Open Access Journals (Sweden)

Christina J. Sun

2016-01-01

Full Text Available Background. Little is known about the role of discrimination on depression among Latino sexual and gender identity minorities. This manuscript examined the relationship between ethnic/racial discrimination and sexual discrimination on clinically significant depressive symptoms among Latino sexual minority men (i.e., gay and bisexual men and other men who have sex with men and Latina transgender women. Methods. A community-based participatory research partnership recruited participants (N = 186; 80.6% cisgender men in North Carolina to a social network-based HIV intervention. Using baseline data, we quantified the amount of perceived discrimination and conducted mixed-effects logistic regression analyses to examine correlates of clinically significant depressive symptoms. Results. A high percentage of participants reported ethnic/racial discrimination (73.7% and sexual discrimination (53.8%. In the multivariable models, ethnic/racial discrimination, sexual discrimination, masculinity, fatalism, and social support were significantly associated with clinically significant depressive symptoms. Discussion. Improving mental health requires multilevel interventions that address pertinent individual, interpersonal, and system level factors.

Orthology prediction at scalable resolution by phylogenetic tree analysis

NARCIS (Netherlands)

Heijden, R.T.J.M. van der; Snel, B.; Noort, V. van; Huynen, M.A.

2007-01-01

BACKGROUND: Orthology is one of the cornerstones of gene function prediction. Dividing the phylogenetic relations between genes into either orthologs or paralogs is however an oversimplification. Already in two-species gene-phylogenies, the complicated, non-transitive nature of phylogenetic

Place of birth effects on self-reported discrimination: Variations by type of discrimination.

Science.gov (United States)

Brondolo, Elizabeth; Rahim, Reanne; Grimaldi, Stephanie; Ashraf, Amina; Bui, Nini; Schwartz, Joseph

2015-11-01

Researchers have suggested that perceptions of discrimination may vary depending on place of birth and the length of time spent living in the U.S., variables related to acculturation. However, the existing literature provides a mixed picture, with data suggesting that the effects of acculturation on perceptions of discrimination vary by race and other sociodemographic factors. This study evaluated the role of place of birth (POB: defined as U.S.-born vs. foreign-born), age at immigration, and length of residence in the U.S. on self-reported discrimination in a sample of urban-dwelling Asian and Black adults (n= 1454). Analyses examined POB effects on different types of discrimination including race-related stigmatization, exclusion, threat, and workplace discrimination. Sociodemographic variables (including age, gender, employment status and education level) were tested as potential moderators of the relationship between POB and discrimination. The results revealed a significant main effect for POB on discrimination, with U.S.-born individuals reporting significantly more discrimination than foreign-born individuals, although the effect was reduced when sociodemographic variables were controlled. Across the sample, POB effects were seen only for race-related stigmatization and exclusion, not for threat and workplace discrimination. With the exception of limited effects for gender, sociodemographic variables did not moderate these effects. Younger age at immigration and greater years of residence in the U.S. were also positively associated with higher levels of perceived discrimination. These findings suggest increasing acculturation may shape the experience and perception of racial and ethnic discrimination.

Place of birth effects on self-reported discrimination: Variations by type of discrimination

Science.gov (United States)

Brondolo, Elizabeth; Rahim, Reanne; Grimaldi, Stephanie; Ashraf, Amina; Bui, Nini; Schwartz, Joseph

2016-01-01

Researchers have suggested that perceptions of discrimination may vary depending on place of birth and the length of time spent living in the U.S., variables related to acculturation. However, the existing literature provides a mixed picture, with data suggesting that the effects of acculturation on perceptions of discrimination vary by race and other sociodemographic factors. This study evaluated the role of place of birth (POB: defined as U.S.-born vs. foreign-born), age at immigration, and length of residence in the U.S. on self-reported discrimination in a sample of urban-dwelling Asian and Black adults (n= 1454). Analyses examined POB effects on different types of discrimination including race-related stigmatization, exclusion, threat, and workplace discrimination. Sociodemographic variables (including age, gender, employment status and education level) were tested as potential moderators of the relationship between POB and discrimination. The results revealed a significant main effect for POB on discrimination, with U.S.-born individuals reporting significantly more discrimination than foreign-born individuals, although the effect was reduced when sociodemographic variables were controlled. Across the sample, POB effects were seen only for race-related stigmatization and exclusion, not for threat and workplace discrimination. With the exception of limited effects for gender, sociodemographic variables did not moderate these effects. Younger age at immigration and greater years of residence in the U.S. were also positively associated with higher levels of perceived discrimination. These findings suggest increasing acculturation may shape the experience and perception of racial and ethnic discrimination. PMID:27647943

Hybrid generative-discriminative approach to age-invariant face recognition

Science.gov (United States)

Sajid, Muhammad; Shafique, Tamoor

2018-03-01

Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

Applying phylogenetic analysis to viral livestock diseases: moving beyond molecular typing.

Science.gov (United States)

Olvera, Alex; Busquets, Núria; Cortey, Marti; de Deus, Nilsa; Ganges, Llilianne; Núñez, José Ignacio; Peralta, Bibiana; Toskano, Jennifer; Dolz, Roser

2010-05-01

Changes in livestock production systems in recent years have altered the presentation of many diseases resulting in the need for more sophisticated control measures. At the same time, new molecular assays have been developed to support the diagnosis of animal viral disease. Nucleotide sequences generated by these diagnostic techniques can be used in phylogenetic analysis to infer phenotypes by sequence homology and to perform molecular epidemiology studies. In this review, some key elements of phylogenetic analysis are highlighted, such as the selection of the appropriate neutral phylogenetic marker, the proper phylogenetic method and different techniques to test the reliability of the resulting tree. Examples are given of current and future applications of phylogenetic reconstructions in viral livestock diseases. Copyright 2009 Elsevier Ltd. All rights reserved.

Psilocybin modulates functional connectivity of the amygdala during emotional face discrimination.

Science.gov (United States)

Grimm, O; Kraehenmann, R; Preller, K H; Seifritz, E; Vollenweider, F X

2018-04-24

Recent studies suggest that the antidepressant effects of the psychedelic 5-HT2A receptor agonist psilocybin are mediated through its modulatory properties on prefrontal and limbic brain regions including the amygdala. To further investigate the effects of psilocybin on emotion processing networks, we studied for the first-time psilocybin's acute effects on amygdala seed-to-voxel connectivity in an event-related face discrimination task in 18 healthy volunteers who received psilocybin and placebo in a double-blind balanced cross-over design. The amygdala has been implicated as a salience detector especially involved in the immediate response to emotional face content. We used beta-series amygdala seed-to-voxel connectivity during an emotional face discrimination task to elucidate the connectivity pattern of the amygdala over the entire brain. When we compared psilocybin to placebo, an increase in reaction time for all three categories of affective stimuli was found. Psilocybin decreased the connectivity between amygdala and the striatum during angry face discrimination. During happy face discrimination, the connectivity between the amygdala and the frontal pole was decreased. No effect was seen during discrimination of fearful faces. Thus, we show psilocybin's effect as a modulator of major connectivity hubs of the amygdala. Psilocybin decreases the connectivity between important nodes linked to emotion processing like the frontal pole or the striatum. Future studies are needed to clarify whether connectivity changes predict therapeutic effects in psychiatric patients. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.

Reconstruction of phylogenetic trees of prokaryotes using maximal common intervals.

Science.gov (United States)

Heydari, Mahdi; Marashi, Sayed-Amir; Tusserkani, Ruzbeh; Sadeghi, Mehdi

2014-10-01

One of the fundamental problems in bioinformatics is phylogenetic tree reconstruction, which can be used for classifying living organisms into different taxonomic clades. The classical approach to this problem is based on a marker such as 16S ribosomal RNA. Since evolutionary events like genomic rearrangements are not included in reconstructions of phylogenetic trees based on single genes, much effort has been made to find other characteristics for phylogenetic reconstruction in recent years. With the increasing availability of completely sequenced genomes, gene order can be considered as a new solution for this problem. In the present work, we applied maximal common intervals (MCIs) in two or more genomes to infer their distance and to reconstruct their evolutionary relationship. Additionally, measures based on uncommon segments (UCS's), i.e., those genomic segments which are not detected as part of any of the MCIs, are also used for phylogenetic tree reconstruction. We applied these two types of measures for reconstructing the phylogenetic tree of 63 prokaryotes with known COG (clusters of orthologous groups) families. Similarity between the MCI-based (resp. UCS-based) reconstructed phylogenetic trees and the phylogenetic tree obtained from NCBI taxonomy browser is as high as 93.1% (resp. 94.9%). We show that in the case of this diverse dataset of prokaryotes, tree reconstruction based on MCI and UCS outperforms most of the currently available methods based on gene orders, including breakpoint distance and DCJ. We additionally tested our new measures on a dataset of 13 closely-related bacteria from the genus Prochlorococcus. In this case, distances like rearrangement distance, breakpoint distance and DCJ proved to be useful, while our new measures are still appropriate for phylogenetic reconstruction. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

One tree to link them all: a phylogenetic dataset for the European tetrapoda.

Science.gov (United States)

Roquet, Cristina; Lavergne, Sébastien; Thuiller, Wilfried

2014-08-08

Since the ever-increasing availability of phylogenetic informative data, the last decade has seen an upsurge of ecological studies incorporating information on evolutionary relationships among species. However, detailed species-level phylogenies are still lacking for many large groups and regions, which are necessary for comprehensive large-scale eco-phylogenetic analyses. Here, we provide a dataset of 100 dated phylogenetic trees for all European tetrapods based on a mixture of supermatrix and supertree approaches. Phylogenetic inference was performed separately for each of the main Tetrapoda groups of Europe except mammals (i.e. amphibians, birds, squamates and turtles) by means of maximum likelihood (ML) analyses of supermatrix applying a tree constraint at the family (amphibians and squamates) or order (birds and turtles) levels based on consensus knowledge. For each group, we inferred 100 ML trees to be able to provide a phylogenetic dataset that accounts for phylogenetic uncertainty, and assessed node support with bootstrap analyses. Each tree was dated using penalized-likelihood and fossil calibration. The trees obtained were well-supported by existing knowledge and previous phylogenetic studies. For mammals, we modified the most complete supertree dataset available on the literature to include a recent update of the Carnivora clade. As a final step, we merged the phylogenetic trees of all groups to obtain a set of 100 phylogenetic trees for all European Tetrapoda species for which data was available (91%). We provide this phylogenetic dataset (100 chronograms) for the purpose of comparative analyses, macro-ecological or community ecology studies aiming to incorporate phylogenetic information while accounting for phylogenetic uncertainty.

Convergent evolution of gene networks by single-gene duplications in higher eukaryotes.

Science.gov (United States)

Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

2004-03-01

By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix-loop-helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks emerging through single-gene duplications, the dominant importance of molecular modularity in the bottom-up construction of complex biological entities, and the convergent evolution of networks.

Assessing the relationships between phylogenetic and functional singularities in sharks (Chondrichthyes).

Science.gov (United States)

Cachera, Marie; Le Loc'h, François

2017-08-01

The relationships between diversity and ecosystem functioning have become a major focus of science. A crucial issue is to estimate functional diversity, as it is intended to impact ecosystem dynamics and stability. However, depending on the ecosystem, it may be challenging or even impossible to directly measure ecological functions and thus functional diversity. Phylogenetic diversity was recently under consideration as a proxy for functional diversity. Phylogenetic diversity is indeed supposed to match functional diversity if functions are conservative traits along evolution. However, in case of adaptive radiation and/or evolutive convergence, a mismatch may appear between species phylogenetic and functional singularities. Using highly threatened taxa, sharks, this study aimed to explore the relationships between phylogenetic and functional diversities and singularities. Different statistical computations were used in order to test both methodological issue (phylogenetic reconstruction) and overall a theoretical questioning: the predictive power of phylogeny for function diversity. Despite these several methodological approaches, a mismatch between phylogeny and function was highlighted. This mismatch revealed that (i) functions are apparently nonconservative in shark species, and (ii) phylogenetic singularity is not a proxy for functional singularity. Functions appeared to be not conservative along the evolution of sharks, raising the conservational challenge to identify and protect both phylogenetic and functional singular species. Facing the current rate of species loss, it is indeed of major importance to target phylogenetically singular species to protect genetic diversity and also functionally singular species in order to maintain particular functions within ecosystem.

SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

Institute of Scientific and Technical Information of China (English)

无

2008-01-01

Quadratic Discrimination Function(QDF)is commonly used in speech emotion recognition,which proceeds on the premise that the input data is normal distribution.In this Paper,we propose a transformation to normalize the emotional features,then derivate a Modified QDF(MQDF) to speech emotion recognition.Features based on prosody and voice quality are extracted and Principal Component Analysis Neural Network (PCANN) is used to reduce dimension of the feature vectors.The results show that voice quality features are effective supplement for recognition.and the method in this paper could improve the recognition ratio effectively.

Species divergence and phylogenetic variation of ecophysiological traits in lianas and trees.

Science.gov (United States)

Rios, Rodrigo S; Salgado-Luarte, Cristian; Gianoli, Ernesto

2014-01-01

The climbing habit is an evolutionary key innovation in plants because it is associated with enhanced clade diversification. We tested whether patterns of species divergence and variation of three ecophysiological traits that are fundamental for plant adaptation to light environments (maximum photosynthetic rate [A(max)], dark respiration rate [R(d)], and specific leaf area [SLA]) are consistent with this key innovation. Using data reported from four tropical forests and three temperate forests, we compared phylogenetic distance among species as well as the evolutionary rate, phylogenetic distance and phylogenetic signal of those traits in lianas and trees. Estimates of evolutionary rates showed that R(d) evolved faster in lianas, while SLA evolved faster in trees. The mean phylogenetic distance was 1.2 times greater among liana species than among tree species. Likewise, estimates of phylogenetic distance indicated that lianas were less related than by chance alone (phylogenetic evenness across 63 species), and trees were more related than expected by chance (phylogenetic clustering across 71 species). Lianas showed evenness for R(d), while trees showed phylogenetic clustering for this trait. In contrast, for SLA, lianas exhibited phylogenetic clustering and trees showed phylogenetic evenness. Lianas and trees showed patterns of ecophysiological trait variation among species that were independent of phylogenetic relatedness. We found support for the expected pattern of greater species divergence in lianas, but did not find consistent patterns regarding ecophysiological trait evolution and divergence. R(d) followed the species-level pattern, i.e., greater divergence/evolution in lianas compared to trees, while the opposite occurred for SLA and no pattern was detected for A(max). R(d) may have driven lianas' divergence across forest environments, and might contribute to diversification in climber clades.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

Science.gov (United States)

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction

The Evolution of Reputation-Based Cooperation in Regular Networks

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Tatsuya Sasaki

2017-01-01

Full Text Available Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules—shunning, image scoring, stern judging, and simple standing—and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule—simple standing—is the most robust among the four assessment rules in promoting cooperation in regular networks.

Spatial phylogenetics of the vascular flora of Chile.

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Scherson, Rosa A; Thornhill, Andrew H; Urbina-Casanova, Rafael; Freyman, William A; Pliscoff, Patricio A; Mishler, Brent D

2017-07-01

Current geographic patterns of biodiversity are a consequence of the evolutionary history of the lineages that comprise them. This study was aimed at exploring how evolutionary features of the vascular flora of Chile are distributed across the landscape. Using a phylogeny at the genus level for 87% of the Chilean vascular flora, and a geographic database of sample localities, we calculated phylogenetic diversity (PD), phylogenetic endemism (PE), relative PD (RPD), and relative PE (RPE). Categorical Analyses of Neo- and Paleo-Endemism (CANAPE) were also performed, using a spatial randomization to assess statistical significance. A cluster analysis using range-weighted phylogenetic turnover was used to compare among grid cells, and with known Chilean bioclimates. PD patterns were concordant with known centers of high taxon richness and the Chilean biodiversity hotspot. In addition, several other interesting areas of concentration of evolutionary history were revealed as potential conservation targets. The south of the country shows areas of significantly high RPD and a concentration of paleo-endemism, and the north shows areas of significantly low PD and RPD, and a concentration of neo-endemism. Range-weighted phylogenetic turnover shows high congruence with the main macrobioclimates of Chile. Even though the study was done at the genus level, the outcome provides an accurate outline of phylogenetic patterns that can be filled in as more fine-scaled information becomes available. Copyright © 2017 Elsevier Inc. All rights reserved.

Robustness of ancestral sequence reconstruction to phylogenetic uncertainty.

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Hanson-Smith, Victor; Kolaczkowski, Bryan; Thornton, Joseph W

2010-09-01

Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny--typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial.

Recursive Neural Networks in Quark/Gluon Tagging

CERN Multimedia

CERN. Geneva

2018-01-01

Vidyo contribution Based on the natural tree-like structure of jet sequential clustering, the recursive neural networks (RecNNs) embed jet clustering history recursively as in natural language processing. We explore the performance of RecNN in quark/gluon discrimination. The results show that RecNNs work better than the baseline BDT by a few percent in gluon rejection at the working point of 50\\% quark acceptance. We also experimented on some relevant aspects which might influence the performance of networks. It shows that even only particle flow identification as input feature without any extra information on momentum or angular position is already giving a fairly good result, which indicates that most of the information for q/g discrimination is already included in the tree-structure itself.

Load Balancing Issues with Constructing Phylogenetic Trees using Neighbour-Joining Algorithm

International Nuclear Information System (INIS)

Al Mamun, S M

2012-01-01

Phylogenetic tree construction is one of the most important and interesting problems in bioinformatics. Constructing an efficient phylogenetic tree has always been a research issue. It needs to consider both the correctness and the speed of the tree construction. In this paper, we implemented the neighbour-joining algorithm, using Message Passing Interface (MPI) for constructing the phylogenetic tree. Performance is efficacious, comparing to the best sequential algorithm. From this paper, it would be clear to the researchers that how load balance can make a great effect for constructing phylogenetic trees using neighbour-joining algorithm.

Efficient Detection of Repeating Sites to Accelerate Phylogenetic Likelihood Calculations.

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Kobert, K; Stamatakis, A; Flouri, T

2017-03-01

The phylogenetic likelihood function (PLF) is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection, and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory savings attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 12-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the PLF currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation. [Algorithms; maximum likelihood; phylogenetic likelihood function; phylogenetics]. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Single-trial multisensory memories affect later auditory and visual object discrimination.

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Thelen, Antonia; Talsma, Durk; Murray, Micah M

2015-05-01

Multisensory memory traces established via single-trial exposures can impact subsequent visual object recognition. This impact appears to depend on the meaningfulness of the initial multisensory pairing, implying that multisensory exposures establish distinct object representations that are accessible during later unisensory processing. Multisensory contexts may be particularly effective in influencing auditory discrimination, given the purportedly inferior recognition memory in this sensory modality. The possibility of this generalization and the equivalence of effects when memory discrimination was being performed in the visual vs. auditory modality were at the focus of this study. First, we demonstrate that visual object discrimination is affected by the context of prior multisensory encounters, replicating and extending previous findings by controlling for the probability of multisensory contexts during initial as well as repeated object presentations. Second, we provide the first evidence that single-trial multisensory memories impact subsequent auditory object discrimination. Auditory object discrimination was enhanced when initial presentations entailed semantically congruent multisensory pairs and was impaired after semantically incongruent multisensory encounters, compared to sounds that had been encountered only in a unisensory manner. Third, the impact of single-trial multisensory memories upon unisensory object discrimination was greater when the task was performed in the auditory vs. visual modality. Fourth, there was no evidence for correlation between effects of past multisensory experiences on visual and auditory processing, suggestive of largely independent object processing mechanisms between modalities. We discuss these findings in terms of the conceptual short term memory (CSTM) model and predictive coding. Our results suggest differential recruitment and modulation of conceptual memory networks according to the sensory task at hand. Copyright �

Phylogenetic Relationships among Species of Phellinus sensu stricto, Cause of White Trunk Rot of Hardwoods, from Northern North America

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Nicholas J. Brazee

2015-11-01

Full Text Available Species in Phellinus s.s. are some of the most important wood-decaying fungal pathogens in northern temperate forests, yet data on species incidence in North America remains limited. Therefore, phylogenetic analyses were performed using four loci (ITS, nLSU, tef1 and rpb2 with isolates representing 13 species. Results of phylogenetic analyses using maximum likelihood and Bayesian inference revealed that eight species of Phellinus s.s. occur in North America, and include: P. alni, P. arctostaphyli, P. betulinus, P. lundellii, P. nigricans, P. tremulae and two undescribed species, P. NA1 and P. NA2. Meanwhile, P. tuberculosus, P. igniarius s.s., P. populicola, P. laevigatus s.s. and P. orienticus were not detected and appear restricted to Europe and/or Asia. The tef1 dataset outperformed all other loci used and was able to discriminate among all 13 of the currently known Phellinus s.s. species with significant statistical support. The internal transcribed spacer (ITS region performed well but a high level of intraspecific variation could lead to inflated taxa recognition. Phellinus alni exhibited the broadest host range, as demonstrated previously, and appears to be the most common species in northern hardwood (Acer-Betula-Fagus, northern floodplain (Fraxinus-Populus-Ulmus and coastal alder (Alnus forests of North America.

Changes in neural network homeostasis trigger neuropsychiatric symptoms.

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Winkelmann, Aline; Maggio, Nicola; Eller, Joanna; Caliskan, Gürsel; Semtner, Marcus; Häussler, Ute; Jüttner, René; Dugladze, Tamar; Smolinsky, Birthe; Kowalczyk, Sarah; Chronowska, Ewa; Schwarz, Günter; Rathjen, Fritz G; Rechavi, Gideon; Haas, Carola A; Kulik, Akos; Gloveli, Tengis; Heinemann, Uwe; Meier, Jochen C

2014-02-01

The mechanisms that regulate the strength of synaptic transmission and intrinsic neuronal excitability are well characterized; however, the mechanisms that promote disease-causing neural network dysfunction are poorly defined. We generated mice with targeted neuron type-specific expression of a gain-of-function variant of the neurotransmitter receptor for glycine (GlyR) that is found in hippocampectomies from patients with temporal lobe epilepsy. In this mouse model, targeted expression of gain-of-function GlyR in terminals of glutamatergic cells or in parvalbumin-positive interneurons persistently altered neural network excitability. The increased network excitability associated with gain-of-function GlyR expression in glutamatergic neurons resulted in recurrent epileptiform discharge, which provoked cognitive dysfunction and memory deficits without affecting bidirectional synaptic plasticity. In contrast, decreased network excitability due to gain-of-function GlyR expression in parvalbumin-positive interneurons resulted in an anxiety phenotype, but did not affect cognitive performance or discriminative associative memory. Our animal model unveils neuron type-specific effects on cognition, formation of discriminative associative memory, and emotional behavior in vivo. Furthermore, our data identify a presynaptic disease-causing molecular mechanism that impairs homeostatic regulation of neural network excitability and triggers neuropsychiatric symptoms.

Mycorrhizae support oaks growing in a phylogenetically distant neighbourhood

NARCIS (Netherlands)

Yguel, B.; Courty, P.E.; Jactel, H.; Pan, X.; Butenschoen, O.; Murray, P.J.; Prinzing, A.

2014-01-01

Host-plants may rarely leave their ancestral niche and in which case they tend to be surrounded by phylogenetically distant neighbours. Phylogenetically isolated host-plants might share few mutualists with their neighbours and might suffer from a decrease in mutualist support. In addition host

Mnemonic discrimination relates to perforant path integrity: An ultra-high resolution diffusion tensor imaging study.

Science.gov (United States)

Bennett, Ilana J; Stark, Craig E L

2016-03-01

Pattern separation describes the orthogonalization of similar inputs into unique, non-overlapping representations. This computational process is thought to serve memory by reducing interference and to be mediated by the dentate gyrus of the hippocampus. Using ultra-high in-plane resolution diffusion tensor imaging (hrDTI) in older adults, we previously demonstrated that integrity of the perforant path, which provides input to the dentate gyrus from entorhinal cortex, was associated with mnemonic discrimination, a behavioral outcome designed to load on pattern separation. The current hrDTI study assessed the specificity of this perforant path integrity-mnemonic discrimination relationship relative to other cognitive constructs (identified using a factor analysis) and white matter tracts (hippocampal cingulum, fornix, corpus callosum) in 112 healthy adults (20-87 years). Results revealed age-related declines in integrity of the perforant path and other medial temporal lobe (MTL) tracts (hippocampal cingulum, fornix). Controlling for global effects of brain aging, perforant path integrity related only to the factor that captured mnemonic discrimination performance. Comparable integrity-mnemonic discrimination relationships were also observed for the hippocampal cingulum and fornix. Thus, whereas perforant path integrity specifically relates to mnemonic discrimination, mnemonic discrimination may be mediated by a broader MTL network. Copyright © 2015 Elsevier Inc. All rights reserved.

Phylogenetic and Metabolic Tracking of Gut Microbiota during Perinatal Development.

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Federica Del Chierico

Full Text Available The colonization and development of gut microbiota immediately after birth is highly variable and depends on several factors, such as delivery mode and modality of feeding during the first months of life. A cohort of 31 mother and neonate pairs, including 25 at-term caesarean (CS and 6 vaginally (V delivered neonates (DNs, were included in this study and 121 meconium/faecal samples were collected at days 1 through 30 following birth. Operational taxonomic units (OTUs were assessed in 69 stool samples by phylogenetic microarray HITChip and inter- and intra-individual distributions were established by inter-OTUs correlation matrices and OTUs co-occurrence or co-exclusion networks. 1H-NMR metabolites were determined in 70 stool samples, PCA analysis was performed on 55 CS DNs samples, and metabolome/OTUs co-correlations were assessed in 45 CS samples, providing an integrated map of the early microbiota OTUs-metabolome. A microbiota "core" of OTUs was identified that was independent of delivery mode and lactation stage, suggesting highly specialized communities that act as seminal colonizers of microbial networks. Correlations among OTUs, metabolites, and OTUs-metabolites revealed metabolic profiles associated with early microbial ecological dynamics, maturation of milk components, and host physiology.

Socially-Tolerable Discrimination

OpenAIRE

Amegashie, J. Atsu

2008-01-01

History is replete with overt discrimination on the basis of race, gender, age, citizenship, ethnicity, marital status, academic performance, health status, volume of market transactions, religion, sexual orientation, etc. However, these forms of discrimination are not equally tolerable. For example, discrimination based on immutable or prohibitively unalterable characteristics such as race, gender, or ethnicity is much less acceptable. Why? I develop a simple rent-seeking model of conflict w...

HIV forensics: pitfalls and acceptable standards in the use of phylogenetic analysis as evidence in criminal investigations of HIV transmission.

Science.gov (United States)

Bernard, E J; Azad, Y; Vandamme, A M; Weait, M; Geretti, A M

2007-09-01

Phylogenetic analysis - the study of the genetic relatedness between HIV strains - has recently been used in criminal prosecutions as evidence of responsibility for HIV transmission. In these trials, the expert opinion of virologists has been of critical importance. Phylogenetic analysis of HIV gene sequences is complex and its findings do not achieve the levels of certainty obtained with the forensic analysis of human DNA. Although two individuals may carry HIV strains that are closely related, these will not necessarily be unique to the two parties and could extend to other persons within the same transmission network. For forensic purposes, phylogenetic analysis should be conducted under strictly controlled conditions by laboratories with relevant expertise applying rigorous methods. It is vitally important to include the right controls, which should be epidemiologically and temporally relevant to the parties under investigation. Use of inappropriate controls can exaggerate any relatedness between the virus strains of the complainant and defendant as being strikingly unique. It will be often difficult to obtain the relevant controls. If convenient but less appropriate controls are used, interpretation of the findings should be tempered accordingly. Phylogenetic analysis cannot prove that HIV transmission occurred directly between two individuals. However, it can exonerate individuals by demonstrating that the defendant carries a virus strain unrelated to that of the complainant. Expert witnesses should acknowledge the limitations of the inferences that might be made and choose the correct language in both written and verbal testimony.

Whole Genome Phylogenetic Tree Reconstruction using Colored de Bruijn Graphs

OpenAIRE

Lyman, Cole

2017-01-01

We present kleuren, a novel assembly-free method to reconstruct phylogenetic trees using the Colored de Bruijn Graph. kleuren works by constructing the Colored de Bruijn Graph and then traversing it, finding bubble structures in the graph that provide phylogenetic signal. The bubbles are then aligned and concatenated to form a supermatrix, from which a phylogenetic tree is inferred. We introduce the algorithm that kleuren uses to accomplish this task, and show its performance on reconstructin...

Racial/Ethnic Workplace Discrimination

Science.gov (United States)

Chavez, Laura J.; Ornelas, India J.; Lyles, Courtney R.; Williams, Emily C.

2014-01-01

Background Experiences of discrimination are associated with tobacco and alcohol use, and work is a common setting where individuals experience racial/ethnic discrimination. Few studies have evaluated the association between workplace discrimination and these behaviors, and none have described associations across race/ethnicity. Purpose To examine the association between workplace discrimination and tobacco and alcohol use in a large, multistate sample of U.S. adult respondents to the Behavioral Risk Factor Surveillance System survey Reactions to Race Module (2004–2010). Methods Multivariable logistic regression analyses evaluated cross-sectional associations between self-reported workplace discrimination and tobacco (current and daily smoking) and alcohol use (any and heavy use, and binge drinking) among all participants and stratified by race/ethnicity, adjusting for relevant covariates. Data were analyzed in 2013. Results Among respondents, 70,080 completed the workplace discrimination measure. Discrimination was more common among black non-Hispanic (21%), Hispanic (12%), and other race respondents (11%) than white non-Hispanics (4%) (pdiscrimination was associated with current smoking (risk ratio [RR]=1.32, 95% CI=1.19, 1.47), daily smoking (RR=1.41, 95% CI=1.24, 1.61), and heavy drinking (RR=1.11, 95% CI=1.01, 1.22), but not binge or any drinking. Among Hispanics, workplace discrimination was associated with increased heavy and binge drinking, but not any alcohol use or smoking. Workplace discrimination among black non-Hispanics and white Non-Hispanics was associated with increased current and daily smoking, but not alcohol outcomes. Conclusions Workplace discrimination is common, associated with smoking and alcohol use, and merits further policy attention given the impact of these behaviors on morbidity and mortality. PMID:25441232

Distance-Based Phylogenetic Methods Around a Polytomy.

Science.gov (United States)

Davidson, Ruth; Sullivant, Seth

2014-01-01

Distance-based phylogenetic algorithms attempt to solve the NP-hard least-squares phylogeny problem by mapping an arbitrary dissimilarity map representing biological data to a tree metric. The set of all dissimilarity maps is a Euclidean space properly containing the space of all tree metrics as a polyhedral fan. Outputs of distance-based tree reconstruction algorithms such as UPGMA and neighbor-joining are points in the maximal cones in the fan. Tree metrics with polytomies lie at the intersections of maximal cones. A phylogenetic algorithm divides the space of all dissimilarity maps into regions based upon which combinatorial tree is reconstructed by the algorithm. Comparison of phylogenetic methods can be done by comparing the geometry of these regions. We use polyhedral geometry to compare the local nature of the subdivisions induced by least-squares phylogeny, UPGMA, and neighbor-joining when the true tree has a single polytomy with exactly four neighbors. Our results suggest that in some circumstances, UPGMA and neighbor-joining poorly match least-squares phylogeny.

The power and pitfalls of HIV phylogenetics in public health.

Science.gov (United States)

Brooks, James I; Sandstrom, Paul A

2013-07-25

Phylogenetics is the application of comparative studies of genetic sequences in order to infer evolutionary relationships among organisms. This tool can be used as a form of molecular epidemiology to enhance traditional population-level communicable disease surveillance. Phylogenetic study has resulted in new paradigms being created in the field of communicable diseases and this commentary aims to provide the reader with an explanation of how phylogenetics can be used in tracking infectious diseases. Special emphasis will be placed upon the application of phylogenetics as a tool to help elucidate HIV transmission patterns and the limitations to these methods when applied to forensic analysis. Understanding infectious disease epidemiology in order to prevent new transmissions is the sine qua non of public health. However, with increasing epidemiological resolution, there may be an associated potential loss of privacy to the individual. It is within this context that we aim to promote the discussion on how to use phylogenetics to achieve important public health goals, while at the same time protecting the rights of the individual.

Neutron-gamma discrimination in mixed field by pulse shape discriminator

International Nuclear Information System (INIS)

Sharghi Ido, A.; Shahriari, M.; Etaati, G. R.

2009-01-01

In this study, a pulse shape discriminator, incorporating zero-crossing method has been developed. The separate measurements with 241 Am-Be and 252 Cf sources undertaken by BC501A liquid have shown that the purposed and the common-used pulse shape discriminator's are in good agreement. The improved characteristics of the presented pulse shape discriminator are FOM=1.36 at a threshold of 60 ke Vee and 1.5μsec dead time which allows the count rates up to 50 k Hz

Parallel or convergent evolution in human population genomic data revealed by genotype networks

OpenAIRE

Vahdati, Ali R; Wagner, Andreas

2016-01-01

Background Genotype networks are representations of genetic variation data that are complementary to phylogenetic trees. A genotype network is a graph whose nodes are genotypes (DNA sequences) with the same broadly defined phenotype. Two nodes are connected if they differ in some minimal way, e.g., in a single nucleotide. Results We analyze human genome variation data from the 1,000 genomes project, and construct haploid genotype (haplotype) networks for 12,235 protein coding genes. The struc...

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

Science.gov (United States)

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

Neural networks applied to discriminate botanical origin of honeys.

Science.gov (United States)

Anjos, Ofélia; Iglesias, Carla; Peres, Fátima; Martínez, Javier; García, Ángela; Taboada, Javier

2015-05-15

The aim of this work is develop a tool based on neural networks to predict the botanical origin of honeys using physical and chemical parameters. The managed database consists of 49 honey samples of 2 different classes: monofloral (almond, holm oak, sweet chestnut, eucalyptus, orange, rosemary, lavender, strawberry trees, thyme, heather, sunflower) and multifloral. The moisture content, electrical conductivity, water activity, ashes content, pH, free acidity, colorimetric coordinates in CIELAB space (L(∗), a(∗), b(∗)) and total phenols content of the honey samples were evaluated. Those properties were considered as input variables of the predictive model. The neural network is optimised through several tests with different numbers of neurons in the hidden layer and also with different input variables. The reduced error rates (5%) allow us to conclude that the botanical origin of honey can be reliably and quickly known from the colorimetric information and the electrical conductivity of honey. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Universal Phylogenetic Tree.

Science.gov (United States)

Offner, Susan

2001-01-01

Presents a universal phylogenetic tree suitable for use in high school and college-level biology classrooms. Illustrates the antiquity of life and that all life is related, even if it dates back 3.5 billion years. Reflects important evolutionary relationships and provides an exciting way to learn about the history of life. (SAH)

Evolution of the brain and phylogenetic development of Mrican ...

African Journals Online (AJOL)

Evolution of the brain and phylogenetic development of Mrican Bovidae. Henriette Oboussier. Zoological Institute and Museum, University of Hamburg. Evidence drawn from the study of 270 brains of 54 species and subspecies of African Bovidae makes it possible to base phylogenetic relationships on the similarities in the ...

Orthology prediction at scalable resolution by phylogenetic tree analysis

Directory of Open Access Journals (Sweden)

Huynen Martijn A

2007-03-01

Full Text Available Abstract Background Orthology is one of the cornerstones of gene function prediction. Dividing the phylogenetic relations between genes into either orthologs or paralogs is however an oversimplification. Already in two-species gene-phylogenies, the complicated, non-transitive nature of phylogenetic relations results in inparalogs and outparalogs. For situations with more than two species we lack semantics to specifically describe the phylogenetic relations, let alone to exploit them. Published procedures to extract orthologous groups from phylogenetic trees do not allow identification of orthology at various levels of resolution, nor do they document the relations between the orthologous groups. Results We introduce "levels of orthology" to describe the multi-level nature of gene relations. This is implemented in a program LOFT (Levels of Orthology From Trees that assigns hierarchical orthology numbers to genes based on a phylogenetic tree. To decide upon speciation and gene duplication events in a tree LOFT can be instructed either to perform classical species-tree reconciliation or to use the species overlap between partitions in the tree. The hierarchical orthology numbers assigned by LOFT effectively summarize the phylogenetic relations between genes. The resulting high-resolution orthologous groups are depicted in colour, facilitating visual inspection of (large trees. A benchmark for orthology prediction, that takes into account the varying levels of orthology between genes, shows that the phylogeny-based high-resolution orthology assignments made by LOFT are reliable. Conclusion The "levels of orthology" concept offers high resolution, reliable orthology, while preserving the relations between orthologous groups. A Windows as well as a preliminary Java version of LOFT is available from the LOFT website http://www.cmbi.ru.nl/LOFT.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

Science.gov (United States)

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

DISCRIMINATION OF WOMEN IN THE LABOUR MARKET OF SR AND MODELS OF DISCRIMINATION

OpenAIRE

Ján Vravec; Radovan Baèík

2012-01-01

IThe paper deals with the problem of women’s discrimination in the labour market. Significant differences, among women and men in the labour market, are especially in unemployment rate in reward system, and high horizontal and vertical segregation of women. The aspects of discrimination arise despite of existing legislation, which gender discrimination strictly prohibits. An analysis of arguments, consequences and models of women’s discrimination in the labour market can significantly help to...

Neural networks and statistical learning

CERN Document Server

Du, Ke-Lin

2014-01-01

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics

Directory of Open Access Journals (Sweden)

von Haeseler Arndt

2004-06-01

Full Text Available Abstract Background Most analysis programs for inferring molecular phylogenies are difficult to use, in particular for researchers with little programming experience. Results TREEFINDER is an easy-to-use integrative platform-independent analysis environment for molecular phylogenetics. In this paper the main features of TREEFINDER (version of April 2004 are described. TREEFINDER is written in ANSI C and Java and implements powerful statistical approaches for inferring gene tree and related analyzes. In addition, it provides a user-friendly graphical interface and a phylogenetic programming language. Conclusions TREEFINDER is a versatile framework for analyzing phylogenetic data across different platforms that is suited both for exploratory as well as advanced studies.

Quantum-state discrimination

International Nuclear Information System (INIS)

Roa, Luis; Retamal, Juan Carlos; Saavedra, Carlos

2002-01-01

A proposal for a physical implementation of a quantum-state discrimination protocol using an ion in a linear trap is studied, where two nonorthogonal quantum states are codified using two electronic states of the ion. In addition, a protocol is given for discriminating superpositions of nonorthogonal entangled states between ions inside widely separated optical cavities. The discrimination protocol is extended to the case of N linearly independent nonorthogonal quantum states lying in a space of 2N-1 dimensions

Perceived discrimination: why applicants and employees expect and perceive discrimination

NARCIS (Netherlands)

Abu Ghazaleh, N.

2012-01-01

In this dissertation we have investigated perceptions of discrimination. We have shown discrimination exists in the eyes of applicants and employees and especially when from an ethnic minority group. There are psychological variables that influence these perceptions differently for minority and

Unstable networks among women in academe: the legal case of Shyamala Rajender.

Science.gov (United States)

Kohlstedt, S; Fischer, S

2009-01-01

Scientific networks are often credited with bringing about institutional change and professional advancement, but less attention has been paid to their instability and occasional failures. In the 1970s optimism among academic women was high as changing US policies on sex discrimination in the workplace, including higher education, seemed to promise equity. Encouraged by colleagues, Shyamala Rajender charged the University of Minnesota with sex discrimination when if failed to consider her for a tenure-track position. The widely cited case of this chemist was not, however, settled easily and involved nearly a decade of university grievance procedures and litigation that grew to a class action lawsuit. As the case gained national attention and internal resistance stiffened, the clusters of women who had been encouraging flickered, faded and sometimes regrouped. A negotiated settlement (consent decree) ended Rajender's case, and it opened the door for hundreds of other to present their grievances regarding gender discrimination. Networks and support groups proved important but also unstable for individuals who sought equity before and during the implementation of the decree. The Rajender case thus exposes the painful, balky and inevitably contentious process of fighting discrimination. It also demonstrates the power and limits of institutions and litigation, as well as the possibilities and disappointments of informal and formal women's networks.

Remote unambiguous discrimination of linearly independent symmetric d-level quantum states

International Nuclear Information System (INIS)

Chen Libing; Liu Yuhua; Tan Peng; Lu Hong

2009-01-01

A set of linearly independent nonorthogonal symmetric d-level quantum states can be discriminated remotely and unambiguously with the aid of two-level Einstein-Podolsky-Rosen (EPR) states. We present a scheme for such a kind of remote unambiguous quantum state discrimination (UD). The probability of discrimination is in agreement with the optimal probability for local unambiguous discrimination among d symmetric states (Chefles and Barnettt 1998 Phys. Lett. A 250 223). This scheme consists of a remote generalized measurement described by a positive operator valued measurement (POVM). This remote POVM can be realized by performing a nonlocal 2d x 2d unitary operation on two spatially separated systems, one is the qudit which is encoded by one of the d symmetric nonorthogonal states to be distinguished and the other is an ancillary qubit, and a conventional local von Neumann orthogonal measurement on the ancilla. By decomposing the evolution process from the initial state to the final state, we construct a quantum network for realizing the remote POVM with a set of two-level nonlocal controlled-rotation gates, and thus provide a feasible physical means to realize the remote UD. A two-level nonlocal controlled-rotation gate can be implemented by using a two-level EPR pair in addition to local operations and classical communications (LOCCs)

Phylogenetic trees in bioinformatics

Energy Technology Data Exchange (ETDEWEB)

Burr, Tom L [Los Alamos National Laboratory

2008-01-01

Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.

Turnover of plant lineages shapes herbivore phylogenetic beta diversity along ecological gradients.

Science.gov (United States)

Pellissier, Loïc; Ndiribe, Charlotte; Dubuis, Anne; Pradervand, Jean-Nicolas; Salamin, Nicolas; Guisan, Antoine; Rasmann, Sergio

2013-05-01

Understanding drivers of biodiversity patterns is of prime importance in this era of severe environmental crisis. More diverse plant communities have been postulated to represent a larger functional trait-space, more likely to sustain a diverse assembly of herbivore species. Here, we expand this hypothesis to integrate environmental, functional and phylogenetic variation of plant communities as factors explaining the diversity of lepidopteran assemblages along elevation gradients in the Swiss Western Alps. According to expectations, we found that the association between butterflies and their host plants is highly phylogenetically structured. Multiple regression analyses showed the combined effect of climate, functional traits and phylogenetic diversity in structuring butterfly communities. Furthermore, we provide the first evidence that plant phylogenetic beta diversity is the major driver explaining butterfly phylogenetic beta diversity. Along ecological gradients, the bottom up control of herbivore diversity is thus driven by phylogenetically structured turnover of plant traits as well as environmental variables. © 2013 Blackwell Publishing Ltd/CNRS.

Bayesian phylogenetic estimation of fossil ages.

Science.gov (United States)

Drummond, Alexei J; Stadler, Tanja

2016-07-19

Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular, the fossilized birth-death tree prior and the Lewis-Mk model of discrete morphological evolution allow for the estimation of both divergence times and phylogenetic relationships between fossil and extant taxa. We exploit this statistical framework to investigate the internal consistency of these models by producing phylogenetic estimates of the age of each fossil in turn, within two rich and well-characterized datasets of fossil and extant species (penguins and canids). We find that the estimation accuracy of fossil ages is generally high with credible intervals seldom excluding the true age and median relative error in the two datasets of 5.7% and 13.2%, respectively. The median relative standard error (RSD) was 9.2% and 7.2%, respectively, suggesting good precision, although with some outliers. In fact, in the two datasets we analyse, the phylogenetic estimate of fossil age is on average less than 2 Myr from the mid-point age of the geological strata from which it was excavated. The high level of internal consistency found in our analyses suggests that the Bayesian statistical model employed is an adequate fit for both the geological and morphological data, and provides evidence from real data that the framework used can accurately model the evolution of discrete morphological traits coded from fossil and extant taxa. We anticipate that this approach will have diverse applications beyond divergence time dating, including dating fossils that are temporally unconstrained, testing of the 'morphological clock', and for uncovering potential model misspecification and/or data errors when controversial phylogenetic hypotheses are obtained based on combined divergence dating analyses.This article is part of the themed issue 'Dating species divergences using

Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

Directory of Open Access Journals (Sweden)

Yongbin Chen

Full Text Available Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD, which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

Phylogenetic relationship and Fourier-transform infrared spectroscopy-derived lipid determinants of lifespan parameters in the Saccharomyces cerevisiae yeast.

Science.gov (United States)

Molon, Mateusz; Zebrowski, Jacek

2017-06-01

Yeast ageing has been gaining much attention in gerontology research, yet the process itself is still not entirely clear. One of the constraints related to the use of the Saccharomyces cerevisiae yeast in studies is the ambiguity of the results concerning ageing determinants for different genetic backgrounds. In this paper, we compare reproductive potentials and lifespans of seven widely used haploid laboratory strains differing in daughter cells production capabilities and highlight the importance of choosing an appropriate genotype for the studies on ageing. Moreover, we show here links between post-reproductive lifespan and lipid metabolism, as well as between reproductive potential, reproductive lifespan and phylogenetic relationship. Using FTIR spectroscopy that generated a biochemical fingerprint of cells, coupled with chemometrics, we found that the band of carbonyl (C = O) stretching vibration discriminates the strains according to post-reproductive lifespan. The results indicated that prolonged post-reproductive lifespan was associated with relatively lower amount of fatty acids esterified to phospholipids compared to a free acid pool, thus implying phospholipid metabolism for the post-reproductive lifespan of yeast. In addition, phylogenetic analysis showed a correlation between nucleotide similarity and the reproductive potential or reproductive lifespan, but not to the longevity expressed in time units. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optical-Correlator Neural Network Based On Neocognitron

Science.gov (United States)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

[Research on Rapid Discrimination of Edible Oil by ATR Infrared Spectroscopy].

Science.gov (United States)

Ma, Xiao; Yuan, Hong-fu; Song, Chun-feng; Hu, Ai-qin; Li, Xiao-yu; Zhao, Zhong; Li, Xiu-qin; Guo Zhen; Zhu, Zhi-qiang

2015-07-01

A rapid discrimination method of edible oils, KL-BP model, was proposed by attenuated total reflectance infrared spectroscopy. The model extracts the characteristic of classification from source data by KL and reduces data dimension at the same time. Then the neural network model is constructed by the new data which as the input of the model. 84 edible oil samples which include sesame oil, corn oil, canola oil, blend oil, sunflower oil, peanut oil, olive oil, soybean oil and tea seed oil, were collected and their infrared spectra determined using an ATR FT-IR spectrometer. In order to compare the method performance, principal component analysis (PCA) direct-classification model, KL direct-classification model, PLS-DA model, PCA-BP model and KL-BP model are constructed in this paper. The results show that the recognition rates of PCA, PCA-BP, KL, PLS-DA and KL-BP are 59.1%, 68.2%, 77.3%, 77.3% and 90.9% for discriminating the 9 kinds of edible oils, respectively. KL extracts the eigenvector which make the distance between different class and distance of every class ratio is the largest. So the method can get much more classify information than PCA. BP neural network can effectively enhance the classification ability and accuracy. Taking full of the advantages of KL in extracting more category information in dimension reducing and the features of BP neural network in self-learning, adaptive, nonlinear, the KL-BP method has the best classification ability and recognition accuracy and great importance for rapidly recognizing edible oil in practice.

The Badness of Discrimination

DEFF Research Database (Denmark)

Lippert-Rasmussen, Kasper

2006-01-01

. In this paper I address these issues. First, I offer a taxonomy of discrimination. I then argue that discrimination is bad, when it is, because it harms people. Finally, I criticize a rival, disrespect-based account according to which discrimination is bad regardless of whether it causes harm....

Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees.

Science.gov (United States)

Baste, Julien; Paul, Christophe; Sau, Ignasi; Scornavacca, Celine

2017-04-01

In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree-a tree having its leaves labeled bijectively by elements of X and without degree-2 nodes-called the "species tree." One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g., DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the "concordance" with the input trees. The obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping-but not identical-sets of labels, is called "supertree." In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of "containing as a minor" and "containing as a topological minor" in the graph community. Both problems are known to be fixed parameter tractable in the number of input trees k, by using their expressibility in monadic second-order logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time [Formula: see text], where n is the total size of the input.

Automatic target recognition using a feature-based optical neural network

Science.gov (United States)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

PhyloSift: phylogenetic analysis of genomes and metagenomes.

Science.gov (United States)

Darling, Aaron E; Jospin, Guillaume; Lowe, Eric; Matsen, Frederick A; Bik, Holly M; Eisen, Jonathan A

2014-01-01

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).

PhyloSift: phylogenetic analysis of genomes and metagenomes

Directory of Open Access Journals (Sweden)

Aaron E. Darling

2014-01-01

Full Text Available Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection.In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata.These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454.

Distinguishing mixed quantum states: Minimum-error discrimination versus optimum unambiguous discrimination

International Nuclear Information System (INIS)

Herzog, Ulrike; Bergou, Janos A.

2004-01-01

We consider two different optimized measurement strategies for the discrimination of nonorthogonal quantum states. The first is ambiguous discrimination with a minimum probability of inferring an erroneous result, and the second is unambiguous, i.e., error-free, discrimination with a minimum probability of getting an inconclusive outcome, where the measurement fails to give a definite answer. For distinguishing between two mixed quantum states, we investigate the relation between the minimum-error probability achievable in ambiguous discrimination, and the minimum failure probability that can be reached in unambiguous discrimination of the same two states. The latter turns out to be at least twice as large as the former for any two given states. As an example, we treat the case where the state of the quantum system is known to be, with arbitrary prior probability, either a given pure state, or a uniform statistical mixture of any number of mutually orthogonal states. For this case we derive an analytical result for the minimum probability of error and perform a quantitative comparison with the minimum failure probability

The social network of actors influencing age discrimination in the human resources recruiting process

Directory of Open Access Journals (Sweden)

Aurelian SOFICĂ

2012-06-01

Full Text Available The aim of the paper is to map the area where the social construction of age discrimination in the recruiting process is perceived as taking place, especially those individuals or organized groups with enough power and interest to influence this unethical reality. The research was carried out in 2010 and 2011 in Cluj-Napoca, Romania; it uses multiple qualitative methods (focus-group and interviews and covers three layers of perception: candidate’s perception, employer’s perception and recruiter’s perception. Usually, the main social actors publically perceived as influencing age discrimination in the recruiting process are the employers (as the main responsible, some public institutions (as guardians and the candidates (as victims. The findings of the paper show that the number of social actors perceived as interested and with power by the main social actors (employers and candidates is much higher than the number classically targeted by researchers, reaching 20 or more

Statistical assignment of DNA sequences using Bayesian phylogenetics

DEFF Research Database (Denmark)

Terkelsen, Kasper Munch; Boomsma, Wouter Krogh; Huelsenbeck, John P.

2008-01-01

We provide a new automated statistical method for DNA barcoding based on a Bayesian phylogenetic analysis. The method is based on automated database sequence retrieval, alignment, and phylogenetic analysis using a custom-built program for Bayesian phylogenetic analysis. We show on real data...... that the method outperforms Blast searches as a measure of confidence and can help eliminate 80% of all false assignment based on best Blast hit. However, the most important advance of the method is that it provides statistically meaningful measures of confidence. We apply the method to a re......-analysis of previously published ancient DNA data and show that, with high statistical confidence, most of the published sequences are in fact of Neanderthal origin. However, there are several cases of chimeric sequences that are comprised of a combination of both Neanderthal and modern human DNA....

Continental scale patterns and predictors of fern richness and phylogenetic diversity

Directory of Open Access Journals (Sweden)

Nathalie eNagalingum

2015-04-01

Full Text Available Because ferns have a wide range of habitat preferences and are widely distributed, they are an ideal group for understanding how diversity is distributed. Here we examine fern diversity on a broad-scale using standard and corrected richness measures as well as phylogenetic indices; in addition we determine the environmental predictors of each diversity metric. Using the combined records of Australian herbaria, a dataset of over 60,000 records was obtained for 89 genera to infer richness. A phylogenetic tree of all the genera was constructed and combined with the herbarium records to obtain phylogenetic diversity patterns. A hotspot of both taxic and phylogenetic diversity occurs in the Wet Tropics of northeastern Australia. Although considerable diversity is distributed along the eastern coast, some important regions of diversity are identified only after sample-standardization of richness and through the phylogenetic metric. Of all of the metrics, annual precipitation was identified as the most explanatory variable, in part, in agreement with global and regional fern studies. Precipitation was combined with a different variable for each different metric. For corrected richness, precipitation is combined with temperature seasonality, while correlation of phylogenetic diversity to precipitation plus radiation indicates support for the species-energy hypothesis. Significantly high and significantly low phylogenetic diversity were found in geographically separate areas. These areas are correlated with different climatic conditions such as seasonality in precipitation. The use of phylogenetic metrics identifies additional areas of significant diversity, some of which have not been revealed using traditional taxonomic analyses, suggesting that different ecological and evolutionary processes have operated over the continent. Our study demonstrates that it is possible and vital to incorporate evolutionary metrics when inferring biodiversity hotspots

Perfume Fragrance Discrimination Using Resistance And Capacitance Responses Of Polymer Sensors

Science.gov (United States)

Lima, John Paul Hempel; Vandendriessche, Thomas; Fonseca, Fernando J.; Lammertyn, Jeroen; Nicolai, Bart M.; de Andrade, Adnei Melges

2009-05-01

This work shows a comparison between electrical resistance and capacitance responses of ethanol and five different fragrances using an electronic nose based on conducting polymers. Gas chromatography—mass spectrometry (GC-MS) measurements were performed to evaluate the main differences between the analytes. It is shown that although the fragrances are quite similar in their compositions the sensors are able to discriminate them through PCA (Principal Component Analysis) and ANNs (Artificial Neural Network) analysis.

Ultra-wideband radar sensors and networks

Science.gov (United States)

Leach, Jr., Richard R; Nekoogar, Faranak; Haugen, Peter C

2013-08-06

Ultra wideband radar motion sensors strategically placed in an area of interest communicate with a wireless ad hoc network to provide remote area surveillance. Swept range impulse radar and a heart and respiration monitor combined with the motion sensor further improves discrimination.

Fast algorithms for computing phylogenetic divergence time.

Science.gov (United States)

Crosby, Ralph W; Williams, Tiffani L

2017-12-06

The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. For example a study of 349 primate taxa was estimated to require over 9 months of processing time. In this work, we present a new algorithm, AncestralAge, that significantly improves the performance of the divergence time process. As part of AncestralAge, we demonstrate a new method for the computation of phylogenetic likelihood and our experiments show a 90% improvement in likelihood computation time on the aforementioned dataset of 349 primates taxa with over 60,000 DNA base pairs. Additionally, we show that our new method for the computation of the Bayesian prior on node ages reduces the running time for this computation on the 349 taxa dataset by 99%. Through the use of these new algorithms we open up the ability to perform divergence time inference on large phylogenetic studies.

Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method

Science.gov (United States)

Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.

2017-09-01

Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

Phylogenetics of neotropical Platymiscium (Leguminosae

DEFF Research Database (Denmark)

Saslis-Lagoudakis, C. Haris; Chase, Mark W; Robinson, Daniel N

2008-01-01

Platymiscium is a neotropical legume genus of forest trees in the Pterocarpus clade of the pantropical "dalbergioid" clade. It comprises 19 species (29 taxa), distributed from Mexico to southern Brazil. This study presents a molecular phylogenetic analysis of Platymiscium and allies inferred from...

Phylogenetic relationships among Maloideae species

Science.gov (United States)

The Maloideae is a highly diverse sub-family of the Rosaceae containing several agronomically important species (Malus sp. and Pyrus sp.) and their wild relatives. Previous phylogenetic work within the group has revealed extensive intergeneric hybridization and polyploidization. In order to develop...

Mass discrimination

Energy Technology Data Exchange (ETDEWEB)

Broeckman, A. [Rijksuniversiteit Utrecht (Netherlands)

1978-12-15

In thermal ionization mass spectrometry the phenomenon of mass discrimination has led to the use of a correction factor for isotope ratio-measurements. The correction factor is defined as the measured ratio divided by the true or accepted value of this ratio. In fact this factor corrects for systematic errors of the whole procedure; however mass discrimination is often associated just with the mass spectrometer.

Effect of site-specific heterogeneous evolution on phylogenetic reconstruction: a simple evaluation.

Science.gov (United States)

Cheng, Qiqun; Su, Zhixi; Zhong, Yang; Gu, Xun

2009-07-15

Recent studies have shown that heterogeneous evolution may mislead phylogenetic analysis, which has been neglected for a long time. We evaluate the effect of heterogeneous evolution on phylogenetic analysis, using 18 fish mitogenomic coding sequences as an example. Using the software DIVERGE, we identify 198 amino acid sites that have experienced heterogeneous evolution. After removing these sites, the rest of sites are shown to be virtually homogeneous in the evolutionary rate. There are some differences between phylogenetic trees built with heterogeneous sites ("before tree") and without heterogeneous sites ("after tree"). Our study demonstrates that for phylogenetic reconstruction, an effective approach is to identify and remove sites with heterogeneous evolution, and suggests that researchers can use the software DIVERGE to remove the influence of heterogeneous evolution before reconstructing phylogenetic trees.

Neuronal discrimination capacity

International Nuclear Information System (INIS)

Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

2003-01-01

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

Neuronal discrimination capacity

Energy Technology Data Exchange (ETDEWEB)

Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

2003-12-19

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

Science.gov (United States)

Li, Jing; Fan, Ming; Zhang, Juan; Li, Lihua

2017-03-01

Convolutional neural networks (CNNs) are the state-of-the-art deep learning network architectures that can be used in a range of applications, including computer vision and medical image analysis. It exhibits a powerful representation learning mechanism with an automated design to learn features directly from the data. However, the common 2D CNNs only use the two dimension spatial information without evaluating the correlation between the adjoin slices. In this study, we established a method of 3D CNNs to discriminate between malignant and benign breast tumors. To this end, 143 patients were enrolled which include 66 benign and 77 malignant instances. The MRI images were pre-processed for noise reduction and breast tumor region segmentation. Data augmentation by spatial translating, rotating and vertical and horizontal flipping is applied to the cases to reduce possible over-fitting. A region-of-interest (ROI) and a volume-of-interest (VOI) were segmented in 2D and 3D DCE-MRI, respectively. The enhancement ratio for each MR series was calculated for the 2D and 3D images. The results for the enhancement ratio images in the two series are integrated for classification. The results of the area under the ROC curve(AUC) values are 0.739 and 0.801 for 2D and 3D methods, respectively. The results for 3D CNN which combined 5 slices for each enhancement ratio images achieved a high accuracy(Acc), sensitivity(Sens) and specificity(Spec) of 0.781, 0.744 and 0.823, respectively. This study indicates that 3D CNN deep learning methods can be a promising technology for breast tumor classification without manual feature extraction.

Workplace discrimination: experiences of practicing physicians.

Science.gov (United States)

Coombs, Alice A Tolbert; King, Roderick K

2005-04-01

In response to a growing concern regarding physician discrimination in the workplace, this study was developed to: (1) describe the types of discrimination that exist for the practicing physician and (2) determine which groups of physicians are more likely to experience the various forms of discrimination. Surveys were mailed to 1930 practicing physicians in Massachusetts. Participants were asked if they had encountered discrimination, how significant the discrimination was against a specific group, the frequency of personal discrimination, and the type of discrimination. Factor analysis identified four types of discrimination: career advancement, punitive behaviors, practice barriers and hiring barriers. A total of 445 responses were received (a 24% response rate). Sixty-three percent of responding physicians had experienced some form of discrimination. Respondents were women (46%), racial/ethnic minorities (42%) and international medical graduates (IMGs) (40%). In addition, 26% of those classified as white were also IMGs. Over 60% of respondents believed discrimination against IMGs was very or somewhat significant. Almost 27% of males acknowledged that gender bias against females was very or somewhat significant. IMGs were more likely to indicate that discrimination against IMGs was significant in their current organization. Of U.S. medical graduates (USMGs) 44% reported that discrimination against IMGs in their current organization was significant. Nonwhites were more likely to report that discrimination based on race/ethnicity was significant. Nearly 29% of white respondents also believed that such discrimination was very or somewhat significant. Physicians practicing in academic, research, and private practice sectors experience discrimination based on gender, ethnic/racial, and IMG status.

SNPhylo: a pipeline to construct a phylogenetic tree from huge SNP data.

Science.gov (United States)

Lee, Tae-Ho; Guo, Hui; Wang, Xiyin; Kim, Changsoo; Paterson, Andrew H

2014-02-26

Phylogenetic trees are widely used for genetic and evolutionary studies in various organisms. Advanced sequencing technology has dramatically enriched data available for constructing phylogenetic trees based on single nucleotide polymorphisms (SNPs). However, massive SNP data makes it difficult to perform reliable analysis, and there has been no ready-to-use pipeline to generate phylogenetic trees from these data. We developed a new pipeline, SNPhylo, to construct phylogenetic trees based on large SNP datasets. The pipeline may enable users to construct a phylogenetic tree from three representative SNP data file formats. In addition, in order to increase reliability of a tree, the pipeline has steps such as removing low quality data and considering linkage disequilibrium. A maximum likelihood method for the inference of phylogeny is also adopted in generation of a tree in our pipeline. Using SNPhylo, users can easily produce a reliable phylogenetic tree from a large SNP data file. Thus, this pipeline can help a researcher focus more on interpretation of the results of analysis of voluminous data sets, rather than manipulations necessary to accomplish the analysis.

BLAST-EXPLORER helps you building datasets for phylogenetic analysis

Directory of Open Access Journals (Sweden)

Claverie Jean-Michel

2010-01-01

Full Text Available Abstract Background The right sampling of homologous sequences for phylogenetic or molecular evolution analyses is a crucial step, the quality of which can have a significant impact on the final interpretation of the study. There is no single way for constructing datasets suitable for phylogenetic analysis, because this task intimately depends on the scientific question we want to address, Moreover, database mining softwares such as BLAST which are routinely used for searching homologous sequences are not specifically optimized for this task. Results To fill this gap, we designed BLAST-Explorer, an original and friendly web-based application that combines a BLAST search with a suite of tools that allows interactive, phylogenetic-oriented exploration of the BLAST results and flexible selection of homologous sequences among the BLAST hits. Once the selection of the BLAST hits is done using BLAST-Explorer, the corresponding sequence can be imported locally for external analysis or passed to the phylogenetic tree reconstruction pipelines available on the Phylogeny.fr platform. Conclusions BLAST-Explorer provides a simple, intuitive and interactive graphical representation of the BLAST results and allows selection and retrieving of the BLAST hit sequences based a wide range of criterions. Although BLAST-Explorer primarily aims at helping the construction of sequence datasets for further phylogenetic study, it can also be used as a standard BLAST server with enriched output. BLAST-Explorer is available at http://www.phylogeny.fr